Publications

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  KI in der Robotik. Flexible und anpassbare Systeme durch interaktives Lernen. Beyerer, J.; Kirchner, E.; Andre, E.; Behnke, S.; Bloss, G.; Dzaack, J.; Egloffstein, T.; Griepentrog, H. W.; Gustmann, M.; Hafner, V. V.; Koert, D.; Nüchter, A.; Seyler, J.; Straube, S.; Tchouchenkov, I.; Stryk, O.; Wedler, A.; Wolf-Ostermann, K.; Zimmermann, M. 2025.
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  Die Fähigkeit, Robotiksysteme einfach und intuitiv an Menschen, neue Aufgaben und Kontexte anzupassen, ist essenziell, um das Potenzial dieser Technologie für die Bewältigung vieler Herausforderungen unserer Zeit auszuschöpfen - sei es der Erhalt und Ausbau der Wettbewerbsfähigkeit, technologische Souveränität, demographischer Wandel oder der Aufbau einer Kreislaufwirtschaft. Die rasante Entwicklung im Bereich des maschinellen Lernens der letzten Jahre, aber auch sinkende Kosten bei Robotern und Komponenten sowie die gestiegene Rechenleistung führen zu einem optimistischen Klima in der Robotik. Menschennahe und adaptive Anwendungen der Robotik in sozialen Umgebungen scheinen daher perspektivisch umsetzbar, die bisher nicht oder nur sehr schwer realisierbar waren, beispielsweise im Dienstleistungsbereich, im Handwerk, im Alltag, im Haushalt oder in der Pflege. Dennoch gilt es sicherheitsrelevante Herausforderungen zu adressieren, die die Entwicklung dieser Technologie begleiten. Denn trotz ihres Potenzials für Wirtschaft und Gesellschaft und ihrer technologischen Möglichkeiten bleibt die Gestaltung sicherer und zuverlässiger Roboter ein zentrales Thema, ebenso wie die Frage nach der Wirtschaftlichkeit. Expertinnen und Experten der Arbeitsgruppe Lernfähige Robotiksysteme der Plattform Lernende Systeme widmen sich in diesem Whitepaper dem Thema der interaktiven, lernfähigen Robotik - vornehmlich aus technologischer Sicht unter Berücksichtigung der Aspekte funktionale Sicherheit und Wirtschaftlichkeit. Zunächst werden die technologischen, gesellschaftlichen und wirtschaftlichen Rahmenbedingungen dargestellt, die dieser Technologie eine vielversprechende Zukunft bescheinigen. Was unter lernfähigen und interaktiven Robotiksystemen zu verstehen ist, wird zunächst definiert, und verschiedene Arten des Lernens in der realen wie virtuellen Welt werden vorgestellt. Sieben Anwendungsbeispiele zeigen, wo und wie interaktive, lernfähige Roboter in naher sowie ferner Zukunft unterstützen können - sei es in der Landwirtschaft, im Gesundheitswesen, im Recycling oder im Weltraum. Dabei werden auch Anforderungen und mögliche Hürden benannt. Aus der Bandbreite der Anwendungsfälle werden Synergien, Besonderheiten und Fokusthemen ermittelt, die in Gestaltungsoptionen für Forschung und Entwicklung, für den Transfer und für den gesellschaftlichen Dialog münden. Dies mit Blick auf modulare Komponenten, technische Integration oder Weiterentwicklung von Sicherheitskonzepten sowie Maßnahmen zu Open-Source-Modulbibliotheken, Testumgebungen oder integrierte und partizipative Forschung.

  @misc{LS2025, abstract = {Die Fähigkeit, Robotiksysteme einfach und intuitiv an Menschen, neue Aufgaben und Kontexte anzupassen, ist essenziell, um das Potenzial dieser Technologie für die Bewältigung vieler Herausforderungen unserer Zeit auszuschöpfen - sei es der Erhalt und Ausbau der Wettbewerbsfähigkeit, technologische Souveränität, demographischer Wandel oder der Aufbau einer Kreislaufwirtschaft. Die rasante Entwicklung im Bereich des maschinellen Lernens der letzten Jahre, aber auch sinkende Kosten bei Robotern und Komponenten sowie die gestiegene Rechenleistung führen zu einem optimistischen Klima in der Robotik. Menschennahe und adaptive Anwendungen der Robotik in sozialen Umgebungen scheinen daher perspektivisch umsetzbar, die bisher nicht oder nur sehr schwer realisierbar waren, beispielsweise im Dienstleistungsbereich, im Handwerk, im Alltag, im Haushalt oder in der Pflege. Dennoch gilt es sicherheitsrelevante Herausforderungen zu adressieren, die die Entwicklung dieser Technologie begleiten. Denn trotz ihres Potenzials für Wirtschaft und Gesellschaft und ihrer technologischen Möglichkeiten bleibt die Gestaltung sicherer und zuverlässiger Roboter ein zentrales Thema, ebenso wie die Frage nach der Wirtschaftlichkeit. Expertinnen und Experten der Arbeitsgruppe Lernfähige Robotiksysteme der Plattform Lernende Systeme widmen sich in diesem Whitepaper dem Thema der interaktiven, lernfähigen Robotik - vornehmlich aus technologischer Sicht unter Berücksichtigung der Aspekte funktionale Sicherheit und Wirtschaftlichkeit. Zunächst werden die technologischen, gesellschaftlichen und wirtschaftlichen Rahmenbedingungen dargestellt, die dieser Technologie eine vielversprechende Zukunft bescheinigen. Was unter lernfähigen und interaktiven Robotiksystemen zu verstehen ist, wird zunächst definiert, und verschiedene Arten des Lernens in der realen wie virtuellen Welt werden vorgestellt. Sieben Anwendungsbeispiele zeigen, wo und wie interaktive, lernfähige Roboter in naher sowie ferner Zukunft unterstützen können - sei es in der Landwirtschaft, im Gesundheitswesen, im Recycling oder im Weltraum. Dabei werden auch Anforderungen und mögliche Hürden benannt. Aus der Bandbreite der Anwendungsfälle werden Synergien, Besonderheiten und Fokusthemen ermittelt, die in Gestaltungsoptionen für Forschung und Entwicklung, für den Transfer und für den gesellschaftlichen Dialog münden. Dies mit Blick auf modulare Komponenten, technische Integration oder Weiterentwicklung von Sicherheitskonzepten sowie Maßnahmen zu Open-Source-Modulbibliotheken, Testumgebungen oder integrierte und partizipative Forschung.}, author = {Beyerer, J. and Kirchner, E. and Andre, E. and Behnke, S. and Bloss, G. and Dzaack, J. and Egloffstein, T. and Griepentrog, H. W. and Gustmann, M. and Hafner, V. V. and Koert, D. and N{\"u}chter, A. and Seyler, J. and Straube, S. and Tchouchenkov, I. and Stryk, O. and Wedler, A. and Wolf-Ostermann, K. and Zimmermann, M.}, keywords = {author}, title = {{KI} in der {R}obotik. {F}lexible und anpassbare Systeme durch interaktives {L}ernen}, year = 2025 }
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  SceneFactory: A Workflow-centric and Unified Framework for Incremental Scene Modeling. Yuan, Yijun; Bleier, Michael; Nüchter, Andreas. In IEEE Transactions on Robotics (TRO), pp. 1–20. 2025.
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  We present SceneFactory, a workflow-centric and unified framework for incremental scene modeling, that conveniently supports a wide range of applications, such as (unposed and/or uncalibrated) multi-view depth estimation, LiDAR completion, (dense) RGB-D/RGB-L/Mono/Depth-only reconstruction and SLAM. The workflow-centric design uses multiple blocks as the basis for constructing different production lines. The supported applications, i.e., productions avoid redundancy in their designs. Thus, the focus is placed on each block itself for independent expansion. To support all input combinations, our implementation consists of four building blocks that form SceneFactory: (1) tracking, (2) flexion, (3) depth estimation, and (4) scene reconstruction. The tracking block is based on Mono SLAM and is extended to support RGB-D and RGB-LiDAR (RGB-L) inputs. Flexion is used to convert the depth image (untrackable) into a trackable image. For general-purpose depth estimation, we propose an unposed & uncalibrated multi-view depth estimation model (U2 -MVD) to estimate dense geometry. U2-MVD exploits dense bundle adjustment to solve for poses, intrinsics, and inverse depth. A semantic-aware ScaleCov step is then introduced to complete the multi-view depth. Relying on U2-MVD, SceneFactory both supports user-friendly 3D creation (with just images) and bridges the applications of Dense RGB-D and Dense Mono. For high-quality surface and color reconstruction, we propose Dual-purpose Multi-resolutional Neural Points (DM-NPs) for the first surface accessible Surface Color Field design, where we introduce Improved Point Rasterization (IPR) for point cloud based surface query. We implement and experiment with SceneFactory to demonstrate its broad applicability and high flexibility. Its quality also competes or exceeds the tightly-coupled state of the art approaches in all tasks. We contribute the code to the community

  @article{TRO2025, abstract = {We present SceneFactory, a workflow-centric and unified framework for incremental scene modeling, that conveniently supports a wide range of applications, such as (unposed and/or uncalibrated) multi-view depth estimation, LiDAR completion, (dense) RGB-D/RGB-L/Mono/Depth-only reconstruction and SLAM. The workflow-centric design uses multiple blocks as the basis for constructing different production lines. The supported applications, i.e., productions avoid redundancy in their designs. Thus, the focus is placed on each block itself for independent expansion. To support all input combinations, our implementation consists of four building blocks that form SceneFactory: (1) tracking, (2) flexion, (3) depth estimation, and (4) scene reconstruction. The tracking block is based on Mono SLAM and is extended to support RGB-D and RGB-LiDAR (RGB-L) inputs. Flexion is used to convert the depth image (untrackable) into a trackable image. For general-purpose depth estimation, we propose an unposed & uncalibrated multi-view depth estimation model (U2 -MVD) to estimate dense geometry. U2-MVD exploits dense bundle adjustment to solve for poses, intrinsics, and inverse depth. A semantic-aware ScaleCov step is then introduced to complete the multi-view depth. Relying on U2-MVD, SceneFactory both supports user-friendly 3D creation (with just images) and bridges the applications of Dense RGB-D and Dense Mono. For high-quality surface and color reconstruction, we propose Dual-purpose Multi-resolutional Neural Points (DM-NPs) for the first surface accessible Surface Color Field design, where we introduce Improved Point Rasterization (IPR) for point cloud based surface query. We implement and experiment with SceneFactory to demonstrate its broad applicability and high flexibility. Its quality also competes or exceeds the tightly-coupled state of the art approaches in all tasks. We contribute the code to the community}, author = {Yuan, Yijun and Bleier, Michael and N{\"u}chter, Andreas}, journal = {IEEE Transactions on Robotics (TRO)}, keywords = {myown}, pages = {1-20}, title = {{SceneFactory: A Workflow-centric and Unified Framework for Incremental Scene Modeling}}, year = 2025 }
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  Deep learning on 3D point clouds for fast pose estimation during satellite rendezvous. Renaut, L.; Frei, H.; Nüchter, A. In Acta Astronautica, 232, pp. 231–243. 2025.
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  Light detection and ranging (lidar) is valuable during non-cooperative space rendezvous scenarios. By processing the 3D point clouds, it is possible to provide a navigation solution, consisting of an estimate of the relative pose of the approached spacecraft. To enable a safe rendezvous, the pose estimation has to be precise, but also robust if the output is used as a primary navigation solution. Navigation has to be performed in real-time, and onboard computing hardware has a reduced processing capability. Therefore, the real-time requirement is a main driver of the design. Additionally, a spacecraft often has a symmetrical shape. In this case, the pose estimation method has to account for the fact that multiple attitudes represent the same configuration. This work investigates the use of a point-based neural network, or 3D neural network, for the pose estimation task. This network is integrated in a full pose estimation pipeline, where every component is optimized to achieve real-time requirements on a representative onboard computing hardware. After pre-processing, the neural network produces a relative position and attitude estimation in a single-stage, where the attitude estimation considers the symmetries of the spacecraft. Furthermore, a high-fidelity lidar simulator is used, which enables to generate an extensive synthetic dataset. The method is trained and optimized solely on synthetic data. After training, the pose estimation is evaluated on real lidar data acquired at a hardware-in-the-loop rendezvous facility. Results highlight that the method is accurate and robust, without a loss in performance when evaluated on real data. Finally, the flight-readiness is demonstrated by runtime evaluations on an onboard computer candidate, showing that the method is suited for real-time processing.

  @article{actaastro2025, abstract = {Light detection and ranging (lidar) is valuable during non-cooperative space rendezvous scenarios. By processing the 3D point clouds, it is possible to provide a navigation solution, consisting of an estimate of the relative pose of the approached spacecraft. To enable a safe rendezvous, the pose estimation has to be precise, but also robust if the output is used as a primary navigation solution. Navigation has to be performed in real-time, and onboard computing hardware has a reduced processing capability. Therefore, the real-time requirement is a main driver of the design. Additionally, a spacecraft often has a symmetrical shape. In this case, the pose estimation method has to account for the fact that multiple attitudes represent the same configuration. This work investigates the use of a point-based neural network, or 3D neural network, for the pose estimation task. This network is integrated in a full pose estimation pipeline, where every component is optimized to achieve real-time requirements on a representative onboard computing hardware. After pre-processing, the neural network produces a relative position and attitude estimation in a single-stage, where the attitude estimation considers the symmetries of the spacecraft. Furthermore, a high-fidelity lidar simulator is used, which enables to generate an extensive synthetic dataset. The method is trained and optimized solely on synthetic data. After training, the pose estimation is evaluated on real lidar data acquired at a hardware-in-the-loop rendezvous facility. Results highlight that the method is accurate and robust, without a loss in performance when evaluated on real data. Finally, the flight-readiness is demonstrated by runtime evaluations on an onboard computer candidate, showing that the method is suited for real-time processing.}, author = {Renaut, L. and Frei, H. and N{\"u}chter, A.}, journal = {Acta Astronautica}, keywords = {author}, pages = {231–243}, title = {Deep learning on 3D point clouds for fast pose estimation during satellite rendezvous}, volume = 232, year = 2025 }
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  Delta- and Kalman-filter designs for multi-sensor pose estimation on spherical mobile mapping systems. Arzberger, F.; Schubert, T.; Wiecha, F.; Zevering, J.; Rothe, J.; Borrmann, D.; Montenegro, S.; Nüchter, A. In Robotics and Autonomous Systems (JRAS), 184, p. 104852. 2025.
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  Spherical mobile mapping systems are not thoroughly studied in terms of inertial pose estimation filtering. The underlying inherent rolling motion introduces high angular velocities and aggressive system dynamics around all principal axes. This motion profile also needs different modeling compared to state-of-the-art competitors, which heavily focus on more rotationally-restricted systems such as UAV, handheld, or cars. In this work we compare our previously proposed “Delta-filter”, which was heavily motivated by the sensors inability to provide covariance estimations, with a Kalman-filter design using a covariance model. Both filters fuse two 6-DoF pose estimators with a motion model in real-time, however the designs are theoretically suitable for an arbitrary number of estimators. We evaluate the trajectories against ground truth pose measurement from an OptiTrack™ motion capturing system. Furthermore, as our spherical systems are equipped with laser-scanners, we evaluate the resulting point clouds against ground truth maps available from a Riegl VZ400 terrestrial laser-scanner (TLS). Our source code and datasets can be found on github (Arzberger, 2023).

  @article{RAS2024, abstract = {Spherical mobile mapping systems are not thoroughly studied in terms of inertial pose estimation filtering. The underlying inherent rolling motion introduces high angular velocities and aggressive system dynamics around all principal axes. This motion profile also needs different modeling compared to state-of-the-art competitors, which heavily focus on more rotationally-restricted systems such as UAV, handheld, or cars. In this work we compare our previously proposed “Delta-filter”, which was heavily motivated by the sensors inability to provide covariance estimations, with a Kalman-filter design using a covariance model. Both filters fuse two 6-DoF pose estimators with a motion model in real-time, however the designs are theoretically suitable for an arbitrary number of estimators. We evaluate the trajectories against ground truth pose measurement from an OptiTrack™ motion capturing system. Furthermore, as our spherical systems are equipped with laser-scanners, we evaluate the resulting point clouds against ground truth maps available from a Riegl VZ400 terrestrial laser-scanner (TLS). Our source code and datasets can be found on github (Arzberger, 2023).}, author = {Arzberger, F. and Schubert, T. and Wiecha, F. and Zevering, J. and Rothe, J. and Borrmann, D. and Montenegro, S. and Nüchter, A.}, journal = {Robotics and Autonomous Systems (JRAS)}, keywords = {author}, pages = 104852, title = {Delta- and Kalman-filter designs for multi-sensor pose estimation on spherical mobile mapping systems}, volume = 184, year = 2025 }
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  libBICOS: eine quelloffene Softwarebibliothek mit GPU-Beschleunigung für binäre Korrespondenzsuche zur 3D-Rekonstruktion. Liebender, C.; Bleier, M.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage und des BIMTages 2025, pp. 29–40. Wichmann, 2025.
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  Das folgende Forschungspapier präsentiert eine quelloffene Softwarebibliothek zur binären Korrespondenzsuche (BICOS), die effiziente 3D-Rekonstruktion mittels Stereokameras und strukturiertem Licht ermöglicht. Ausgehend von zwei Stapeln rektifizierter Stereobilder einer Szene die durch statistische Lichtmuster ausgeleuchtet wird, löst die Implementierung das Problem der pixelweisen Korrespondenzsuche. Unsere Implementierung mit GPU-Beschleu- nigung reduziert die Latenz der Tiefenbildberechnung auf weniger als 50 Millisekunden. Ausgehend vom durch DIETRICH ET AL. 2019 eingeführten BICOS-Deskriptor erweitern wir die Flexibilität des Algorithmus bzgl. anwendbarer Lichtprojektion und erhöhen die mögli- che Deskriptorgröße. Schließlich geben wir mittels Laufzeitanalysen und Beispielrekonstruk- tionen einer Stereokamera einen Ausblick auf erreichbare Genauigkeiten und Performanz. Obwohl es viele Implementierungen zur Tiefenbildberechnung auf Basis eines einzelnen Bildpaares gibt, ist dies für Algorithmen auf Basis von Bildstapeln mit strukturiertem Licht nicht der Fall. Deshalb hoffen wir durch die Veröffentlichung unserer Bibliothek den Einstieg in das Thema zu erleichtern. Der Quellcode ist verfügbar unter \url{https://github.com/JMUWRobotics/libBICOS unter der GNU LGPLv3.

  @inproceedings{3DTAGE2025, abstract = {Das folgende Forschungspapier präsentiert eine quelloffene Softwarebibliothek zur binären Korrespondenzsuche (BICOS), die effiziente 3D-Rekonstruktion mittels Stereokameras und strukturiertem Licht ermöglicht. Ausgehend von zwei Stapeln rektifizierter Stereobilder einer Szene die durch statistische Lichtmuster ausgeleuchtet wird, löst die Implementierung das Problem der pixelweisen Korrespondenzsuche. Unsere Implementierung mit GPU-Beschleu- nigung reduziert die Latenz der Tiefenbildberechnung auf weniger als 50 Millisekunden. Ausgehend vom durch DIETRICH ET AL. 2019 eingeführten BICOS-Deskriptor erweitern wir die Flexibilität des Algorithmus bzgl. anwendbarer Lichtprojektion und erhöhen die mögli- che Deskriptorgröße. Schließlich geben wir mittels Laufzeitanalysen und Beispielrekonstruk- tionen einer Stereokamera einen Ausblick auf erreichbare Genauigkeiten und Performanz. Obwohl es viele Implementierungen zur Tiefenbildberechnung auf Basis eines einzelnen Bildpaares gibt, ist dies für Algorithmen auf Basis von Bildstapeln mit strukturiertem Licht nicht der Fall. Deshalb hoffen wir durch die Veröffentlichung unserer Bibliothek den Einstieg in das Thema zu erleichtern. Der Quellcode ist verfügbar unter \url{https://github.com/JMUWRobotics/libBICOS} unter der GNU LGPLv3.}, author = {Liebender, C. and Bleier, M. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage und des BIMTages 2025}, keywords = {author}, month = {02}, pages = {29–40}, publisher = {Wichmann}, title = {{libBICOS: eine quelloffene Softwarebibliothek mit GPU-Beschleunigung für binäre Korrespondenzsuche zur 3D-Rekonstruktion}}, year = 2025 }
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  CNN-based Pose Estimation of a Non-Cooperative Spacecraft with Symmetries from Lidar Point Clouds. Renaut, L.; Frei, H.; Nüchter, A. In IEEE Transactions on Aerospace and Electronic Systems (TAES), 61(2), pp. 1–16. 2025.
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  Light detection and ranging (lidar) sensors provide accurate 3D point clouds for non-cooperative spacecraft pose estimation. Several robust methods such as Iterative Closest Point (ICP) exist to perform a local refinement of the pose starting from an initial estimate. However, finding the initial pose of the spacecraft is a global optimization problem which is challenging to solve in real-time. This is especially true on space hardware with limited computing power. In addition, many spacecrafts have a shape with multiple symmetries, making an unambiguous initial pose estimation impossible. This work introduces a Convolutional Neural Network (CNN) based pose estimation method, accounting for potential symmetries of the target satellite. The point clouds are projected to a 2D depth image before being processed by the network. To generate a sufficient amount of training data, a lidar simulator integrating multiple effects such as reflections or laser beam divergence is developed. While being trained solely on synthetic point clouds, the pose estimation method shows to be precise, efficient and reliable when evaluated on real point clouds taken at a hardware-in-the-loop rendezvous test facility. A runtime evaluation on potential space computing hardware is also performed to demonstrate the applicability of the method to real-time onboard pose estimation.

  @article{TAES2024, abstract = {Light detection and ranging (lidar) sensors provide accurate 3D point clouds for non-cooperative spacecraft pose estimation. Several robust methods such as Iterative Closest Point (ICP) exist to perform a local refinement of the pose starting from an initial estimate. However, finding the initial pose of the spacecraft is a global optimization problem which is challenging to solve in real-time. This is especially true on space hardware with limited computing power. In addition, many spacecrafts have a shape with multiple symmetries, making an unambiguous initial pose estimation impossible. This work introduces a Convolutional Neural Network (CNN) based pose estimation method, accounting for potential symmetries of the target satellite. The point clouds are projected to a 2D depth image before being processed by the network. To generate a sufficient amount of training data, a lidar simulator integrating multiple effects such as reflections or laser beam divergence is developed. While being trained solely on synthetic point clouds, the pose estimation method shows to be precise, efficient and reliable when evaluated on real point clouds taken at a hardware-in-the-loop rendezvous test facility. A runtime evaluation on potential space computing hardware is also performed to demonstrate the applicability of the method to real-time onboard pose estimation.}, author = {Renaut, L. and Frei, H. and N{\"u}chter, A.}, journal = {IEEE Transactions on Aerospace and Electronic Systems (TAES)}, keywords = {author}, month = {04}, number = 2, pages = {1–16}, title = {{CNN}-based {P}ose {E}stimation of a {N}on-{C}ooperative {S}pacecraft with {S}ymmetries from {L}idar {P}oint {C}louds}, volume = 61, year = 2025 }

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  Universal Multi-layer Map Display and Improved Situational Awareness in Real-World Facilities. Edlinger, R.; Nüchter, A. In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’24). New York, USA, 2024.
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  This paper introduces a Universal Multi-layer Map Display designed to enhance situational awareness in real-world facilities like hospitals, factories, or disaster sites. The proposed system integrates multiple layers of spatial and semantic data into a unified, interactive interface, allowing users to navigate complex environments with improved clarity and decision-making capabilities. By combining metric maps, topo- logical maps, and semantic information (e.g., room functions, hazard zones, and live sensor data), the multi-layer map enables operators and robot systems to visualize and interact with real-time data streams intuitively. The research explores the application of this system in dynamic, cluttered environments where real-time mapping and navigation are critical. Key innovations include the fusion of multi-modal sensor data, switching between map layers to suit different operational needs, and integrating context-aware alerts that provide up-to- date insights on environmental changes and potential hazards. The system improves situational awareness by offering a com- prehensive view of the environment, enhancing decision-making and coordination in complex tasks such as emergency response, logistics, and facility management. The results emphasize the importance of multi-layered data representation and intuitive interfaces in environments where spatial awareness is critical to mission success.

  @inproceedings{SSRR2024, abstract = {This paper introduces a Universal Multi-layer Map Display designed to enhance situational awareness in real-world facilities like hospitals, factories, or disaster sites. The proposed system integrates multiple layers of spatial and semantic data into a unified, interactive interface, allowing users to navigate complex environments with improved clarity and decision-making capabilities. By combining metric maps, topo- logical maps, and semantic information (e.g., room functions, hazard zones, and live sensor data), the multi-layer map enables operators and robot systems to visualize and interact with real-time data streams intuitively. The research explores the application of this system in dynamic, cluttered environments where real-time mapping and navigation are critical. Key innovations include the fusion of multi-modal sensor data, switching between map layers to suit different operational needs, and integrating context-aware alerts that provide up-to- date insights on environmental changes and potential hazards. The system improves situational awareness by offering a com- prehensive view of the environment, enhancing decision-making and coordination in complex tasks such as emergency response, logistics, and facility management. The results emphasize the importance of multi-layered data representation and intuitive interfaces in environments where spatial awareness is critical to mission success.}, address = {New York, USA}, author = {Edlinger, R. and N{\"u}chter, A.}, booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '24)}, keywords = {myown}, title = {{Universal Multi-layer Map Display and Improved Situational Awareness in Real-World Facilities}}, year = 2024 }
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  A handheld stereo vision and LiDAR system for outdoor dense RGB-D mapping using depth map completion based on learned priors. Bleier, M.; Yuan, Y.; Nüchter, A. In Proceedings of LowCost3D 2024, of ISPRS Int. Archives Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLVIII-2/W8-2024, pp. 31–36. Brescia, Italy, 2024.
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  This paper proposes a handheld mapping system consisting of a stereo camera setup combined with low-cost automotive LiDAR. The prototype system is applicable to various types of mobile monocular, stereo vision and LiDAR data collection and processing. Capturing dense RGB-D data outdoors with low-cost sensors is challenging, especially when low latency is required. Readily available commercial RGB-D sensors are typically limited to a range of less than 10 m, which is too small to capture large outdoor structures. Currently available low-cost automotive LiDAR scanners feature a suitable range but provide only sparse data. To enable low-latency dense RGB-D scans we augment the sparse LiDAR data with the RGB data stream based on learned models. We apply monocular depth estimation based on a single image and apply scale correction based on learned priors and sparse automotive LiDAR scans. Using the laser scan data, accurate metric information is incorporated directly into the scale estimation stage. For validation, the learning-based depth map completion is compared to traditional LiDAR mapping using scan matching on an outdoor data set acquired with the proposed handheld. While the model-based regression of the sparse LiDAR data produces significantly less accurate results in our experiments, it is able to compute dense RGB-D data from a single sparse 3D scan and monocular RGB image with low latency.

  @inproceedings{LC2024, abstract = {This paper proposes a handheld mapping system consisting of a stereo camera setup combined with low-cost automotive LiDAR. The prototype system is applicable to various types of mobile monocular, stereo vision and LiDAR data collection and processing. Capturing dense RGB-D data outdoors with low-cost sensors is challenging, especially when low latency is required. Readily available commercial RGB-D sensors are typically limited to a range of less than 10 m, which is too small to capture large outdoor structures. Currently available low-cost automotive LiDAR scanners feature a suitable range but provide only sparse data. To enable low-latency dense RGB-D scans we augment the sparse LiDAR data with the RGB data stream based on learned models. We apply monocular depth estimation based on a single image and apply scale correction based on learned priors and sparse automotive LiDAR scans. Using the laser scan data, accurate metric information is incorporated directly into the scale estimation stage. For validation, the learning-based depth map completion is compared to traditional LiDAR mapping using scan matching on an outdoor data set acquired with the proposed handheld. While the model-based regression of the sparse LiDAR data produces significantly less accurate results in our experiments, it is able to compute dense RGB-D data from a single sparse 3D scan and monocular RGB image with low latency.}, address = {Brescia, Italy}, author = {Bleier, M. and Yuan, Y. and N{\"u}chter, A.}, booktitle = {Proceedings of LowCost3D 2024}, keywords = {author}, month = 12, pages = {31–36}, series = {ISPRS Int. Archives Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLVIII-2/W8-2024}, title = {A handheld stereo vision and {LiDAR} system for outdoor dense {RGB-D} mapping using depth map completion based on learned priors}, year = 2024 }
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  libBICOS -- An Open Source GPU-Accelerated Library implementing BInary COrrespondence Search for 3D Reconstruction. Liebender, C.; Bleier, M.; Nüchter, A. In Proceedings of Optical 3D Metrology 2024 (O3DM ’24), of ISPRS Int. Archives Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLVIII-2/W7-2024, pp. 57–64. Brescia, Italy, 2024.
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  In this paper, we present an implementation and publish an open source library for binary correspondence search (BICOS), an efficient method for accurate 3D reconstruction from structured light stereo imagery. Starting with two stacks of stereo-rectified images of a scene illuminated by a statistical light pattern the proposed method solves the problem of a pixelwise correspondence search. Our GPU-accelerated implementation reduces the latency of disparity computation using 7MP images on modern hardware down to 20 milliseconds. Based on the algorithm introduced by Dietrich et al. (2019), we extend their approach by increasing the descriptor size while augmenting postprocessing to increase its applicability on other types of pattern projections. Lastly, we provide benchmarks and example reconstructions using a stereo camera setup combined with an off-the-shelf projector to validate the algorithm’s performance. While many state-of-the-art single-shot stereo implementations are included in common computer vision libraries, high performance multi-shot methods are not broadly available. By publishing this method as a freely available library, in both a CUDA and CPU implementation, we hope for others to quickly gain traction in this field. The source code with build instructions and command-line tooling is available at https://github.com/JMUWRobotics/libBICOS under the GNU LGPLv3.

  @inproceedings{O3DM2024, abstract = {In this paper, we present an implementation and publish an open source library for binary correspondence search (BICOS), an efficient method for accurate 3D reconstruction from structured light stereo imagery. Starting with two stacks of stereo-rectified images of a scene illuminated by a statistical light pattern the proposed method solves the problem of a pixelwise correspondence search. Our GPU-accelerated implementation reduces the latency of disparity computation using 7MP images on modern hardware down to 20 milliseconds. Based on the algorithm introduced by Dietrich et al. (2019), we extend their approach by increasing the descriptor size while augmenting postprocessing to increase its applicability on other types of pattern projections. Lastly, we provide benchmarks and example reconstructions using a stereo camera setup combined with an off-the-shelf projector to validate the algorithm’s performance. While many state-of-the-art single-shot stereo implementations are included in common computer vision libraries, high performance multi-shot methods are not broadly available. By publishing this method as a freely available library, in both a CUDA and CPU implementation, we hope for others to quickly gain traction in this field. The source code with build instructions and command-line tooling is available at https://github.com/JMUWRobotics/libBICOS under the GNU LGPLv3.}, address = {Brescia, Italy}, author = {Liebender, C. and Bleier, M. and N{\"u}chter, A.}, booktitle = {Proceedings of Optical 3D Metrology 2024 (O3DM '24)}, keywords = {myown}, month = 12, pages = {57–64}, series = {ISPRS Int. Archives Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLVIII-2/W7-2024}, title = {{libBICOS – An Open Source GPU-Accelerated Library implementing BInary COrrespondence Search for 3D Reconstruction}}, year = 2024 }
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  Embodied Intelligence in Mining: Leveraging Multi-modal Large Language Model for Autonomous Driving in Mines. Li, Luxi; Li, Yuchen; Zhang, Xiaotong; He, Yuhang; Yang, Jianjian; Tian, Bin; Ai, Yunfeng; Li, Lingxi; Nüchter, A.; Xuanyuan, Zhe. In IEEE Transactions on Intelligent Vehicles (TIV), pp. 1–4. 2024.
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  With computer technology advancing in both software and hardware, the benefits of embodied intelligence are becoming increasingly evident. This robust interactive learning model enables artificial intelligence (AI) to be more flexibly deployed across diverse fields. In recent years, the development of multi-modal large language models (LLMs) has further accelerated the progress of AI, prompting extensive research on how to leverage these advancements to enhance the field of autonomous driving. This perspective believes that embodied intelligence can significantly enhance the application of LLMs, analyzing the new opportunities brought to the mining industry, and emphasizing the potential of their integration to revolutionize various aspects of the field. Meanwhile, This perspective also examines the challenges of deploying embodied agents in mining, while emphasizing their promising future and offering insights into potential research and development avenues.

  @article{TIV2024_1, abstract = {With computer technology advancing in both software and hardware, the benefits of embodied intelligence are becoming increasingly evident. This robust interactive learning model enables artificial intelligence (AI) to be more flexibly deployed across diverse fields. In recent years, the development of multi-modal large language models (LLMs) has further accelerated the progress of AI, prompting extensive research on how to leverage these advancements to enhance the field of autonomous driving. This perspective believes that embodied intelligence can significantly enhance the application of LLMs, analyzing the new opportunities brought to the mining industry, and emphasizing the potential of their integration to revolutionize various aspects of the field. Meanwhile, This perspective also examines the challenges of deploying embodied agents in mining, while emphasizing their promising future and offering insights into potential research and development avenues.}, author = {Li, Luxi and Li, Yuchen and Zhang, Xiaotong and He, Yuhang and Yang, Jianjian and Tian, Bin and Ai, Yunfeng and Li, Lingxi and N{\"u}chter, A. and Xuanyuan, Zhe}, journal = {IEEE Transactions on Intelligent Vehicles (TIV)}, keywords = {model;intelligent}, pages = {1-4}, title = {{Embodied Intelligence in Mining: Leveraging Multi-modal Large Language Model for Autonomous Driving in Mines}}, year = 2024 }
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  Design and evaluation of an UI for astronauts to control mobile robots on planetary surfaces. Arzberger, J.; Zevering, J.; Arzberger, F.; Nüchter, A. In Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC ’24), pp. 74–81. Paredes de Coura, Portugal, 2024.
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  With an advancing plan to send humans on planetary missions again, there will be an increasing need for direct on-surface robot control as interaction between robots and humans will increase with increasing sophistication and complexity of tasks. Remote control from Earth with long delays in communication will not be possible through the direct interaction on the surface. Although a higher degree of autonomy of the robots themselves will also play a role, there is a fundamental lack of interfaces for astronauts to control robots on future planetary missions. This research emerged from participation in the AMADEE-24 Mars simulation by the Austrian Space Forum, which focus on researching future human-robot missions on Mars. We designed and evaluated user interface (UI) prototypes for mobile robots operated by astronauts by using a user-centered design approach and incorporated astronaut feedback. We tested the resulting functional prototype in hypothetical scenarios which demonstrated in a low error rate. This affirms the effectiveness of customized user interfaces for specific mission needs. We advocate for adaptability and user involvement to enhance human-robot interaction for planetary exploration. This work not only addresses the need for intuitive robot control systems but also presents potential UI layouts for future human-robotic mission interfaces.

  @inproceedings{ICARSC2024, abstract = {With an advancing plan to send humans on planetary missions again, there will be an increasing need for direct on-surface robot control as interaction between robots and humans will increase with increasing sophistication and complexity of tasks. Remote control from Earth with long delays in communication will not be possible through the direct interaction on the surface. Although a higher degree of autonomy of the robots themselves will also play a role, there is a fundamental lack of interfaces for astronauts to control robots on future planetary missions. This research emerged from participation in the AMADEE-24 Mars simulation by the Austrian Space Forum, which focus on researching future human-robot missions on Mars. We designed and evaluated user interface (UI) prototypes for mobile robots operated by astronauts by using a user-centered design approach and incorporated astronaut feedback. We tested the resulting functional prototype in hypothetical scenarios which demonstrated in a low error rate. This affirms the effectiveness of customized user interfaces for specific mission needs. We advocate for adaptability and user involvement to enhance human-robot interaction for planetary exploration. This work not only addresses the need for intuitive robot control systems but also presents potential UI layouts for future human-robotic mission interfaces.}, address = {Paredes de Coura, Portugal}, author = {Arzberger, J. and Zevering, J. and Arzberger, F. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC '24)}, keywords = {control;Layout;Prototypes;Human-robot}, pages = {74–81}, title = {Design and evaluation of an UI for astronauts to control mobile robots on planetary surfaces}, year = 2024 }
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  On the 3D Trochoidal Motion Model of LiDAR Sensors Placed Off-Centered Inside Spherical Mobile Mapping Systems . Arzberger, F.; Nüchter, A. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’24). Abu Dhabi, UAE, 2024.
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  We study the motion model of a sensor rigidly mounted inside a ball. Due to the rigid placement inside the ball, the geometry of the sensor trajectory resembles a 3D curate trochoid. A new calibration method for spherical systems estimates the extrinsic parameters of the sensor with respect to the balls center of rotation. We deploy the calibration and motion model on our spherical mobile mapping platform to estimate the trajectory of a LiDAR sensor and compare it to trajectories of state-of-the-art LiDAR-Inertial odometry (LIO) methods. The motion model, which is solely based on IMU measurements, produces comparable results to the LIO methods, sometimes even outperforming them in positional accuracy. Although the LIO methods provide better rotational accuracy due to the utilization of LiDAR data, they struggle to reproduce the trochoidal nature of the trajectory and only provide pose estimations at the LiDAR frequency, whereas the motion model produces a more consistent trochoidal trajectory at the much higher IMU frequency. The results demonstrate the difficulty that current LIO methods have on spherical systems and indicate that our motion model is suitable for overcoming these issues.

  @inproceedings{IROS2022_1, abstract = {We study the motion model of a sensor rigidly mounted inside a ball. Due to the rigid placement inside the ball, the geometry of the sensor trajectory resembles a 3D curate trochoid. A new calibration method for spherical systems estimates the extrinsic parameters of the sensor with respect to the balls center of rotation. We deploy the calibration and motion model on our spherical mobile mapping platform to estimate the trajectory of a LiDAR sensor and compare it to trajectories of state-of-the-art LiDAR-Inertial odometry (LIO) methods. The motion model, which is solely based on IMU measurements, produces comparable results to the LIO methods, sometimes even outperforming them in positional accuracy. Although the LIO methods provide better rotational accuracy due to the utilization of LiDAR data, they struggle to reproduce the trochoidal nature of the trajectory and only provide pose estimations at the LiDAR frequency, whereas the motion model produces a more consistent trochoidal trajectory at the much higher IMU frequency. The results demonstrate the difficulty that current LIO methods have on spherical systems and indicate that our motion model is suitable for overcoming these issues.}, address = {Abu Dhabi, UAE}, author = {Arzberger, F. and N{\"u}chter, A.}, booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '24)}, keywords = {myown}, month = 10, title = {{On the 3D Trochoidal Motion Model of LiDAR Sensors Placed Off-Centered Inside Spherical Mobile Mapping Systems }}, year = 2024 }
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  UWB Anchor Based Localization of a Planetary Rover. Nüchter, A.; Werner, L.; Hesse, M.; Borrmann, D.; Walter, T.; Montenegro, S.; Grömer, G. In Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS ’24). Brisbane, Australia, 2024.
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  Localization of an autonomous mobile robot during planetary exploration is challenging due to the unknown terrain, the difficult lighting conditions and the lack of any global reference such as satellite navigation systems. We present a novel approach for robot localization based on ultra-wideband (UWB) technology. The robot sets up its own reference coordinate system by distributing UWB anchor nodes in the environment via a rocket-propelled launcher system. This allows the creation of a localization space in which UWB measurements are employed to supplement traditional SLAM-based techniques. The system was developed for our involvement in the ESA-ESRIC challenge 2021 and the AMADEE-24, an analog Mars simulation in Armenia by the Austrian Space Forum (ÖWF).

  @inproceedings{ISAIRAS2024, abstract = {Localization of an autonomous mobile robot during planetary exploration is challenging due to the unknown terrain, the difficult lighting conditions and the lack of any global reference such as satellite navigation systems. We present a novel approach for robot localization based on ultra-wideband (UWB) technology. The robot sets up its own reference coordinate system by distributing UWB anchor nodes in the environment via a rocket-propelled launcher system. This allows the creation of a localization space in which UWB measurements are employed to supplement traditional SLAM-based techniques. The system was developed for our involvement in the ESA-ESRIC challenge 2021 and the AMADEE-24, an analog Mars simulation in Armenia by the Austrian Space Forum (ÖWF).}, address = {Brisbane, Australia}, author = {N{\"u}chter, A. and Werner, L. and Hesse, M. and Borrmann, D. and Walter, T. and Montenegro, S. and Gr{\"o}mer, G.}, booktitle = {Proceedings of the International Symposium on Artificial Intelligence, Robotics and Automation in Space (i-SAIRAS '24)}, keywords = {myown}, month = 11, title = {{UWB} {A}nchor {B}ased {L}ocalization of a {P}lanetary {R}over}, year = 2024 }
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  Optimal Number and Positioning of Inertial Measurement Units in Spherical Robots. Bösch, C.; Zevering, J.; Nüchter, A. In Proceedings of the 18th Conference on Intelligent Autonomous Systems (IAS ’23), Vol. 2 of Lecture Notes in Networks and Systems, pp. 509–520. Springer, Seoul, Korea, 2024.
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  Spherical robots are a rather niche part of robotics. Often IMUs are used for orientation determination of those robots. These IMUs are mostly placed in the center of the spherical shape, but for different subtypes of spherical robots, this is not possible due to different drive mechanism. This paper evaluates Inertial Measurement Unit (IMU) configurations for different spherical robot types in terms of orientation determination accuracy in a series of four experiments. We establish the relationship between the accuracy of orientation determination and the following aspects of IMU configurations: (A) the number of IMUs, (B) the distance of an IMU from the center of the sphere, (C) symmetrical placement of IMUs around the sphere’s center, and (D) axial placement. Based on the findings of these experiments, we set up the optimal configurations for the different types of spherical robots.

  @inproceedings{IAS2023, abstract = {Spherical robots are a rather niche part of robotics. Often IMUs are used for orientation determination of those robots. These IMUs are mostly placed in the center of the spherical shape, but for different subtypes of spherical robots, this is not possible due to different drive mechanism. This paper evaluates Inertial Measurement Unit (IMU) configurations for different spherical robot types in terms of orientation determination accuracy in a series of four experiments. We establish the relationship between the accuracy of orientation determination and the following aspects of IMU configurations: (A) the number of IMUs, (B) the distance of an IMU from the center of the sphere, (C) symmetrical placement of IMUs around the sphere’s center, and (D) axial placement. Based on the findings of these experiments, we set up the optimal configurations for the different types of spherical robots.}, address = {Seoul, Korea}, author = {B{\"o}sch, C. and Zevering, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the 18th Conference on Intelligent Autonomous Systems (IAS '23)}, keywords = {myown}, month = {07}, number = 795, pages = {509-520}, publisher = {Springer}, series = {Lecture Notes in Networks and Systems}, title = {{Optimal Number and Positioning of Inertial Measurement Units in Spherical Robots}}, volume = 2, year = 2024 }
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  RIV-SLAM: Radar-Inertial-Velocity optimization based graph SLAM. Wang, D.; May, S.; Nüchter, A. In Proceedings of the 20th IEEE International Conference on Automation Science and Engineering (CASE ’24), pp. 1–8. Bari, Italy, 2024.
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  4D imaging radars, commonly known as 4D radars, deliver comprehensive point cloud data that encap- sulates range, azimuth, elevation, and Doppler velocity in- formation even in harsh environmental conditions, such as rain, snow, smoke, and fog. However, 4D radar data also suffers from high noise and sparsity, which poses great chal- lenges for SLAM applications. This paper presents RIV-SLAM, a complete radar-inertial-velocity optimization-based graph SLAM system designed to exploit the full potential of 4D imaging radar technology. RIV-SLAM consists of four integral components: front-end, loop closure, IMU pre-integration and graph optimization, each optimized to effectively leverage the unique attributes of radar data and tightly coupled with IMU data. This is also the first SLAM system known to us that outputs an optimized ego velocity. This capability ensures reliable ego motion estimation under extreme conditions (e.g., wheel odometry fails). Furthermore, we develop a new ground extraction approach, specifically adapted for the 4D imaging radar, which substantially improves the system’s z-axis accuracy. Comprehensive evaluations of the RIV-SLAM system on a variety of datasets demonstrate its superior performance, significantly surpassing existing state-of-the-art Radar-SLAM frameworks. The code of RIV-SLAM will be released at: RIV- SLAM

  @inproceedings{CASE2023, abstract = {4D imaging radars, commonly known as 4D radars, deliver comprehensive point cloud data that encap- sulates range, azimuth, elevation, and Doppler velocity in- formation even in harsh environmental conditions, such as rain, snow, smoke, and fog. However, 4D radar data also suffers from high noise and sparsity, which poses great chal- lenges for SLAM applications. This paper presents RIV-SLAM, a complete radar-inertial-velocity optimization-based graph SLAM system designed to exploit the full potential of 4D imaging radar technology. RIV-SLAM consists of four integral components: front-end, loop closure, IMU pre-integration and graph optimization, each optimized to effectively leverage the unique attributes of radar data and tightly coupled with IMU data. This is also the first SLAM system known to us that outputs an optimized ego velocity. This capability ensures reliable ego motion estimation under extreme conditions (e.g., wheel odometry fails). Furthermore, we develop a new ground extraction approach, specifically adapted for the 4D imaging radar, which substantially improves the system’s z-axis accuracy. Comprehensive evaluations of the RIV-SLAM system on a variety of datasets demonstrate its superior performance, significantly surpassing existing state-of-the-art Radar-SLAM frameworks. The code of RIV-SLAM will be released at: RIV- SLAM}, address = {Bari, Italy}, author = {Wang, D. and May, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the 20th IEEE International Conference on Automation Science and Engineering (CASE '24)}, keywords = {myown}, month = {09}, pages = {1–8}, title = {{RIV-SLAM: Radar-Inertial-Velocity optimization based graph SLAM}}, year = 2024 }
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  Uni-Fusion: Universal Continuous Mapping. Yuan, Y.; Nüchter, A. In IEEE Transactions on Robotics (T-RO), 40, pp. 1373–1392. 2024.
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  We present Uni-Fusion, a universal continuous mapping framework for surfaces, surface properties (color, infrared, etc.) and more (latent features in contrastive language-image pretraining (CLIP) embedding space, etc.). We propose the first universal implicit encoding model that supports encoding of both geometry and different types of properties (RGB, infrared, features, etc.) without requiring any training. Based on this, our framework divides the point cloud into regular grid voxels and generates a latent feature in each voxel to form a latent implicit map (LIM) for geometries and arbitrary properties. Then, by fusing a local LIM frame-wisely into a global LIM, an incremental reconstruction is achieved. Encoded with corresponding types of data, our LIM is capable of generating continuous surfaces, surface property fields, surface feature fields, and all other possible options. To demonstrate the capabilities of our model, we implement three applications: incremental reconstruction for surfaces and color, 2-D-to-3-D transfer of fabricated properties, and open-vocabulary scene understanding by creating a text CLIP feature field on surfaces. We evaluate Uni-Fusion by comparing it in corresponding applications, from which Uni-Fusion shows high-flexibility in various applications while performing best or being competitive.

  @article{TRO2024, abstract = {We present Uni-Fusion, a universal continuous mapping framework for surfaces, surface properties (color, infrared, etc.) and more (latent features in contrastive language-image pretraining (CLIP) embedding space, etc.). We propose the first universal implicit encoding model that supports encoding of both geometry and different types of properties (RGB, infrared, features, etc.) without requiring any training. Based on this, our framework divides the point cloud into regular grid voxels and generates a latent feature in each voxel to form a latent implicit map (LIM) for geometries and arbitrary properties. Then, by fusing a local LIM frame-wisely into a global LIM, an incremental reconstruction is achieved. Encoded with corresponding types of data, our LIM is capable of generating continuous surfaces, surface property fields, surface feature fields, and all other possible options. To demonstrate the capabilities of our model, we implement three applications: incremental reconstruction for surfaces and color, 2-D-to-3-D transfer of fabricated properties, and open-vocabulary scene understanding by creating a text CLIP feature field on surfaces. We evaluate Uni-Fusion by comparing it in corresponding applications, from which Uni-Fusion shows high-flexibility in various applications while performing best or being competitive.}, author = {Yuan, Y. and N{\"u}chter, A.}, journal = {IEEE Transactions on Robotics (T-RO)}, keywords = {myown}, pages = {1373–1392}, title = {{Uni-Fusion: Universal Continuous Mapping}}, volume = 40, year = 2024 }
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  Covariance Based Terrain Mapping for Autonomous Mobile Robots. Werner, L.; Proenca, P.; Nüchter, A; Brockers, R. In Proceedings of the IEEE International Conference Robotics and Automation (ICRA ’24). Yokohama, Japan, 2024.
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  In this paper, we present a local, robot-centric navigation map optimized for autonomous mobile robots op- erating in unknown environments, enhancing their onboard perception systems for collision-free operation with far look- ahead distances. Utilizing a novel converging covariance cell representation, our approach effectively analyzes hazards such as obstacles and hazardous slopes in both terrestrial and aerial navigation contexts. The new technique specifically targets mapping from stereo scenarios with ultra short baseline and highly oblique viewpoints close to the ground. Our methodology surpasses traditional window-based haz- ard analysis by resolving sub-cell size obstacles and terrain gradients at the individual cell level, thereby avoiding the computational overhead typically associated with such analyses. It leverages a multi-resolution strategy adaptive to the range errors common in stereo vision systems, making it particularly suitable for embedded systems with computational limitations. Functionality includes constant-time queries for height, ob- stacle presence, and slope details, boasting improvements in run time, memory usage, precision, and resolvable obstacle size compared to existing grid-based mapping algorithms. We validate our approach through rigorous simulation and real- world testing. This technique will be used for the local mapping and collision avoidance on NASA’s CADRE lunar rovers.

  @inproceedings{werner2024covariance, abstract = {In this paper, we present a local, robot-centric navigation map optimized for autonomous mobile robots op- erating in unknown environments, enhancing their onboard perception systems for collision-free operation with far look- ahead distances. Utilizing a novel converging covariance cell representation, our approach effectively analyzes hazards such as obstacles and hazardous slopes in both terrestrial and aerial navigation contexts. The new technique specifically targets mapping from stereo scenarios with ultra short baseline and highly oblique viewpoints close to the ground. Our methodology surpasses traditional window-based haz- ard analysis by resolving sub-cell size obstacles and terrain gradients at the individual cell level, thereby avoiding the computational overhead typically associated with such analyses. It leverages a multi-resolution strategy adaptive to the range errors common in stereo vision systems, making it particularly suitable for embedded systems with computational limitations. Functionality includes constant-time queries for height, ob- stacle presence, and slope details, boasting improvements in run time, memory usage, precision, and resolvable obstacle size compared to existing grid-based mapping algorithms. We validate our approach through rigorous simulation and real- world testing. This technique will be used for the local mapping and collision avoidance on NASA’s CADRE lunar rovers.}, address = {Yokohama, Japan}, author = {Werner, L. and Proenca, P. and N{\"u}chter, A and Brockers, R.}, booktitle = {Proceedings of the IEEE International Conference Robotics and Automation (ICRA '24)}, keywords = {myown}, month = {05}, title = {Covariance Based Terrain Mapping for Autonomous Mobile Robots}, year = 2024 }
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  Sora for Smart Mining: Towards Sustainability With Imaginative Intelligence and Parallel Intelligence. Xie, Yuting; Wang, Cong; Liu, Kunhua; Xuanyuan, Zhe; He, Yuhang; Cheng, Hui; Nüchter, A.; Li, Lingxi; Huai, Rouxing; Tang, Shuming; Ma, Siji; Chen, Long. In IEEE Transactions on Intelligent Vehicles, pp. 1–2. 2024.
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  @article{TIV2024, author = {Xie, Yuting and Wang, Cong and Liu, Kunhua and Xuanyuan, Zhe and He, Yuhang and Cheng, Hui and N{\"u}chter, A. and Li, Lingxi and Huai, Rouxing and Tang, Shuming and Ma, Siji and Chen, Long}, journal = {IEEE Transactions on Intelligent Vehicles}, keywords = {Vehicles}, pages = {1–2}, title = {Sora for Smart Mining: Towards Sustainability With Imaginative Intelligence and Parallel Intelligence}, year = 2024 }
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  Inertial LiDAR Motion Distortion Correction on Spherical Mobile Mapping Systems for Planetary Exploration. Heinisch, P.; Arzberger, F.; Nüchter, A. In Proceedings of the International Conference on Space Robotics (iSpaRo ’24). Luxembourg, 2024.
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  In this paper, we present an algorithm countering the motion distortion observed in LiDAR point clouds due to the inherent inertial rotations when recorded with a spherical mobile mapping system. State-of-the-art motion distortion correction algorithms focus on more rotationally restricted systems, such as UAVs, rovers, or cars, where often a “dead-reckoning” approach is utilized to account for the vehicles linear velocity. Thus, the algorithm presented in this paper is based on a motion model for spherical systems, taking only the angular velocities into account. We show, despite explicitly omitting a model for the linear velocity of the scanner, and assuming constant angular velocity between two frames, that our approach outperforms state-of-the-art algorithms which use a false model for the linear velocities. To verify this, we test our algorithm on 3D point clouds recorded with a Livox MID-100 mounted on a spherical mobile mapping system, and compare the accuracy to an algorithm proposed in the Livox-SDK. To do this, we have ground truth point clouds available from a terrestrial laser scanner (TLS). Our algorithm consistently reduces the motion distortion from low (5 Hz) to high (50 Hz) LiDAR sampling frequencies, such that the point clouds are well-suited for further processing steps such as odometry or mapping.

  @inproceedings{ISPARO2024, abstract = {In this paper, we present an algorithm countering the motion distortion observed in LiDAR point clouds due to the inherent inertial rotations when recorded with a spherical mobile mapping system. State-of-the-art motion distortion correction algorithms focus on more rotationally restricted systems, such as UAVs, rovers, or cars, where often a “dead-reckoning” approach is utilized to account for the vehicles linear velocity. Thus, the algorithm presented in this paper is based on a motion model for spherical systems, taking only the angular velocities into account. We show, despite explicitly omitting a model for the linear velocity of the scanner, and assuming constant angular velocity between two frames, that our approach outperforms state-of-the-art algorithms which use a false model for the linear velocities. To verify this, we test our algorithm on 3D point clouds recorded with a Livox MID-100 mounted on a spherical mobile mapping system, and compare the accuracy to an algorithm proposed in the Livox-SDK. To do this, we have ground truth point clouds available from a terrestrial laser scanner (TLS). Our algorithm consistently reduces the motion distortion from low (5 Hz) to high (50 Hz) LiDAR sampling frequencies, such that the point clouds are well-suited for further processing steps such as odometry or mapping.}, address = {Luxembourg}, author = {Heinisch, P. and Arzberger, F. and N{\"u}chter, A.}, booktitle = {Proceedings of the International Conference on Space Robotics (iSpaRo '24)}, keywords = {myown}, month = {05}, title = {Inertial LiDAR Motion Distortion Correction on Spherical Mobile Mapping Systems for Planetary Exploration}, year = 2024 }

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  Delta Filter -- Robust Visual-Inertial Pose Estimation in Real-Time: A Multi-Trajectory Filter on a Spherical Mobile Mapping System. Arzberger, F.; Wiecha, F.; Zevering, J.; Rothe, J.; Borrmann, D.; Montenegro, S.; Nüchter, A. In Proceedings of the 2023 European Conference on Mobile Robots (ECMR ’23), pp. 1–8. 2023.
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  Many state-of-the-art mobile mapping systems accomplish reliable and robust pose estimation utilizing combinations of inertial measurement units (IMUs), global navigation satellite systems (GNSS), visual-inertial- or LiDAR-inertial odometry (VIO/LIO). However, on a spherical mobile mapping system the underlying inherent rolling motion introduces high angular velocities, thus the quality of pose estimates, images, and laser-scans, degrade. In this work we propose a pose filter design that is able to do real-time sensor fusion between two unreliable trajectories into one, more reliable trajectory. It is a simple yet effective filter design that does not require the user to estimate the uncertainty of the sensors. The approach is not limited to spherical robots and theoretically is also suitable for sensor fusion of an arbitrary number of estimators. This work compares this filter against two pose estimation methods on our spherical system: (1) An approach that is based solely on IMU measurements, and (2) stereo-VIO with an Intel® RealSense™ tracking camera. The proposed “Delta” filter takes as input (1), (2), and a motion model. Our implementation gets rid of the drift in (1) and (2), estimates the scale of the trajectory, and deals with slow and fast motion as well as driving curves. Our source code can be found on github [1].

  @inproceedings{ECMR2023, abstract = {Many state-of-the-art mobile mapping systems accomplish reliable and robust pose estimation utilizing combinations of inertial measurement units (IMUs), global navigation satellite systems (GNSS), visual-inertial- or LiDAR-inertial odometry (VIO/LIO). However, on a spherical mobile mapping system the underlying inherent rolling motion introduces high angular velocities, thus the quality of pose estimates, images, and laser-scans, degrade. In this work we propose a pose filter design that is able to do real-time sensor fusion between two unreliable trajectories into one, more reliable trajectory. It is a simple yet effective filter design that does not require the user to estimate the uncertainty of the sensors. The approach is not limited to spherical robots and theoretically is also suitable for sensor fusion of an arbitrary number of estimators. This work compares this filter against two pose estimation methods on our spherical system: (1) An approach that is based solely on IMU measurements, and (2) stereo-VIO with an Intel® RealSense™ tracking camera. The proposed “Delta” filter takes as input (1), (2), and a motion model. Our implementation gets rid of the drift in (1) and (2), estimates the scale of the trajectory, and deals with slow and fast motion as well as driving curves. Our source code can be found on github [1].}, author = {Arzberger, F. and Wiecha, F. and Zevering, J. and Rothe, J. and Borrmann, D. and Montenegro, S. and Nüchter, A.}, booktitle = {Proceedings of the 2023 European Conference on Mobile Robots (ECMR '23)}, keywords = {myown}, month = {09}, pages = {1-8}, title = {Delta Filter – Robust Visual-Inertial Pose Estimation in Real-Time: A Multi-Trajectory Filter on a Spherical Mobile Mapping System}, year = 2023 }
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  Visual odometry and mapping under poor visibility conditions using a stereo infrared thermal imaging system. Edlinger, R.; Himmelbauer, G.; Zauner, G.; Nüchter, A. In Proceedings of the IS\&T International Symposium on Electronic Imaging Science and Technology, of Electronic Imaging, pp. 325–1. Society for Imaging Science and Technology, San Francisco, CA, USA, 2023.
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  In the past decades, developments in the field of computer vision have made both the software and hardware more capable and more easily accessible. This has enabled otherwise complex vision systems to be used in other fields, such as autonomous robotics. Although vision systems in the visible light spectrum are commonplace in robotics nowadays, the thermal spectrum is still rarely used, even though it offers certain advantages. A thermal camera can sense the temperature of objects, is independent of illumination and can actually see through heavy smoke and fog. This makes it a useful tool in particular in the field of rescue robotics, where poor vision conditions are to be expected. In this paper, the feasibility of using two thermal cameras in a stereo vision setup to map indoor scenes is to be examined. It is meant to allow an autonomous robot to perceive its indoor surroundings as a 3D space, even in poor vision conditions. The biggest challenges are the calibration of thermal cameras and the proper filtering of the raw image and the resulting disparity map. Simple and easily implemented solutions are proposed for each of these issues.

  @inproceedings{EI2023a, abstract = {In the past decades, developments in the field of computer vision have made both the software and hardware more capable and more easily accessible. This has enabled otherwise complex vision systems to be used in other fields, such as autonomous robotics. Although vision systems in the visible light spectrum are commonplace in robotics nowadays, the thermal spectrum is still rarely used, even though it offers certain advantages. A thermal camera can sense the temperature of objects, is independent of illumination and can actually see through heavy smoke and fog. This makes it a useful tool in particular in the field of rescue robotics, where poor vision conditions are to be expected. In this paper, the feasibility of using two thermal cameras in a stereo vision setup to map indoor scenes is to be examined. It is meant to allow an autonomous robot to perceive its indoor surroundings as a 3D space, even in poor vision conditions. The biggest challenges are the calibration of thermal cameras and the proper filtering of the raw image and the resulting disparity map. Simple and easily implemented solutions are proposed for each of these issues.}, address = {San Francisco, CA, USA}, author = {Edlinger, R. and Himmelbauer, G. and Zauner, G. and N{\"u}chter, A.}, booktitle = {Proceedings of the IS\&T International Symposium on Electronic Imaging Science and Technology}, keywords = {myown}, month = {01}, pages = {325-1–325-7}, publisher = {Society for Imaging Science and Technology}, series = {Electronic Imaging}, title = {Visual odometry and mapping under poor visibility conditions using a stereo infrared thermal imaging system}, year = 2023 }
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  Dynamics of spherical telescopic linear driven rotation robots. Zevering, J.; Borrmann, D.; Nüchter, A. In 17th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA ’23). ESA, Noordwijk, Netherlands, 2023.
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  Lunar caves are promising features for long-term and permanent human presence on the moon. However, given their inaccessibility to imaging from survey satellites, the concrete environment within the underground cavities is not well known. Thus, to further the efforts of human presence on the moon, these caves are to be explored by robotic systems. However, a set of environmental factors make this exploration particularly challenging. Among those are the very fine lunar dust that damages exposed sensors and actuators and the unknown composition of the surface and obstacles within the cavity. One robotic system that is particularly fit to meet these challenges is that of a spherical robot, as the exterior shell completely separates the sensors and actuators from the hazardous environment. This work introduces the mathematical description in the form of a dynamic model of a novel locomotion approach for this form factor that adds additional functionality. A set of telescopic linearly extending rods moves the robot using a combination of pushing away from the ground and leveraging the gravitational torque. The approach allows the system to locomote, overcome objects by hoisting its center of gravity on top, and transform into a terrestrial laser scanner by using the rods as a tripod.

  @inproceedings{ASTRA2023, abstract = {Lunar caves are promising features for long-term and permanent human presence on the moon. However, given their inaccessibility to imaging from survey satellites, the concrete environment within the underground cavities is not well known. Thus, to further the efforts of human presence on the moon, these caves are to be explored by robotic systems. However, a set of environmental factors make this exploration particularly challenging. Among those are the very fine lunar dust that damages exposed sensors and actuators and the unknown composition of the surface and obstacles within the cavity. One robotic system that is particularly fit to meet these challenges is that of a spherical robot, as the exterior shell completely separates the sensors and actuators from the hazardous environment. This work introduces the mathematical description in the form of a dynamic model of a novel locomotion approach for this form factor that adds additional functionality. A set of telescopic linearly extending rods moves the robot using a combination of pushing away from the ground and leveraging the gravitational torque. The approach allows the system to locomote, overcome objects by hoisting its center of gravity on top, and transform into a terrestrial laser scanner by using the rods as a tripod.}, address = {Noordwijk, Netherlands}, author = {Zevering, J. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {17th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA '23)}, keywords = {myown}, month = 10, publisher = {ESA}, title = {{Dynamics of spherical telescopic linear driven rotation robots}}, year = 2023 }
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  Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction. Edlinger, R.; Nüchter, A. In Proceedings of the 32st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 1121–1128. Busan, Korea, 2023.
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  The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions. To address this challenge, this paper proposes a method called ”Feel the Point Clouds” that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot’s behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner. The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.

  @inproceedings{ROMAN2023, abstract = {The field of human-robot interaction has been rapidly advancing in recent years, as robots are increasingly being integrated into various aspects of human life. However, for robots to effectively collaborate with humans, it is crucial that they have a deep understanding of the environment in which they operate. In particular, the ability to predict traversability and detect tactile information is crucial for enhancing the safety and efficiency of human-robot interactions. To address this challenge, this paper proposes a method called ”Feel the Point Clouds” that use point clouds to predict traversability and detect tactile terrain information for a tracked rescue robot. This information can be used to adjust the robot’s behavior and movements in real-time, allowing it to interact with the environment in a more intuitive and safe manner. The experimental results of the proposed method are evaluated in various scenarios and demonstrate its effectiveness in improving human-robot interaction and visualization for a more accurate and intuitive understanding of the environment.}, address = {Busan, Korea}, author = {Edlinger, R. and N{\"u}chter, A.}, booktitle = {Proceedings of the 32st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)}, keywords = {myown}, month = {08}, pages = {1121–1128}, title = {Feel the Point Clouds: Traversability Prediction and Tactile Terrain Detection Information for an Improved Human-Robot Interaction}, year = 2023 }
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  Transfer Learning for LULC Classification on multi-modal data in the Amazon Basin. Hell, M.; Brandmeier, M.; and A. Nüchter. In Proceedings of the EGU General Assembly 2023. Vienna, Austria \& Online, 2023.
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  @inproceedings{EGU2023, address = {Vienna, Austria \& Online}, author = {Hell, M. and Brandmeier, M. and and A. N{\"u}chter}, booktitle = {Proceedings of the EGU General Assembly 2023}, keywords = {author}, month = {04}, number = {EGU2023-15020}, title = {{Transfer Learning for LULC Classification on multi-modal data in the Amazon Basin}}, year = 2023 }
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  Infradar-Localization: single-chip infrared- and radar-based Monte Carlo localization. Wang, D.; Masannek, M.; May, S.; Nüchter, A. In Proceedings of the 19th IEEE International Conference on Automation Science and Engineering (CASE ’23), pp. 1–8. Auckland, New Zealand, 2023.
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  Infradar-Localization: single-chip infrared- and radar-based Monte Carlo localization. This paper proposes a novel approach for indoor robot localization that leverages a fusion of information from single-chip infrared (Time-of-Flight) and radar sensors. The aim of our research is the development of a cost-effective and lightweight system that can achieve high-precision robot localization. Unlike traditional localization methods based on LiDARs or cameras, our proposed system uses single-chip infrared and radar sensors to overcome the limitations of high cost and bulky hardware. Specifically, we employ a Doppler radar-based velocity motion model for the estimation of the robot's ego-motion, eliminating the need for additional sensors such as IMU or wheel encoders. Next, we describe a hybrid sensor model for single-chip infrared and radar sensors that provides robust and accurate environmental perception with dynamic outlier removal. Finally, we integrate these components into a Monte Carlo localization framework to generate accurate real-time estimation of the robot's position and orientation. This is the first time a single-chip infrared and radar fusion based framework has been applied to robot localization, to the best of our knowledge. Through a comprehensive experimental evaluation, we demonstrate the system's high accuracy and efficiency, achieving an average localization error of 9 cm in diverse indoor environments. This remarkable performance, combined with the low-cost and lightweight nature of our proposed solution, positions it as a highly promising alternative for a wide range of applications, including robotics, smart homes, and autonomous vehicles. The significant advancements of this novel approach offer vast potential to revolutionize the field of localization, enabling more precise and cost-effective navigation systems.

  @inproceedings{CASE2023, abstract = {Infradar-Localization: single-chip infrared- and radar-based Monte Carlo localization. This paper proposes a novel approach for indoor robot localization that leverages a fusion of information from single-chip infrared (Time-of-Flight) and radar sensors. The aim of our research is the development of a cost-effective and lightweight system that can achieve high-precision robot localization. Unlike traditional localization methods based on LiDARs or cameras, our proposed system uses single-chip infrared and radar sensors to overcome the limitations of high cost and bulky hardware. Specifically, we employ a Doppler radar-based velocity motion model for the estimation of the robot's ego-motion, eliminating the need for additional sensors such as IMU or wheel encoders. Next, we describe a hybrid sensor model for single-chip infrared and radar sensors that provides robust and accurate environmental perception with dynamic outlier removal. Finally, we integrate these components into a Monte Carlo localization framework to generate accurate real-time estimation of the robot's position and orientation. This is the first time a single-chip infrared and radar fusion based framework has been applied to robot localization, to the best of our knowledge. Through a comprehensive experimental evaluation, we demonstrate the system's high accuracy and efficiency, achieving an average localization error of 9 cm in diverse indoor environments. This remarkable performance, combined with the low-cost and lightweight nature of our proposed solution, positions it as a highly promising alternative for a wide range of applications, including robotics, smart homes, and autonomous vehicles. The significant advancements of this novel approach offer vast potential to revolutionize the field of localization, enabling more precise and cost-effective navigation systems.}, address = {Auckland, New Zealand}, author = {Wang, D. and Masannek, M. and May, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the 19th IEEE International Conference on Automation Science and Engineering (CASE '23)}, keywords = {myown}, month = {09}, pages = {1–8}, title = {Infradar-Localization: single-chip infrared- and radar-based Monte Carlo localization}, year = 2023 }
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  Inverse Kinematics of an Anthropomorphic 6R Robot Manipulator Based on a Simple Geometric Approach for Embedded Systems. Anschober, M.; Edlinger, R.; Froschauer, R.; Nüchter, A. In Robotics, 12(4). MDPI, 2023.
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  This manuscript presents an efficient algorithm for solving the inverse kinematics problem of a 6R robot manipulator to be deployed on embedded control hardware. The proposed method utilizes the geometric relationship between the end-effector and the base of the manipulator, resulting in a computationally efficient solution. The approach aims to minimize computational complexity and memory consumption while maintaining the accuracy and real-time performance demonstrated by simulations and verified by experimental results on an embedded system. Furthermore, the manipulator is analyzed in terms of singularities, limits, the workspace, and general solvability. Due to the simplicity of the algorithm, a platform-independent implementation is possible. As a result, the average calculation time is reduced by a factor of five to eight and the average error is decreased by a factor of fifty compared to a powerful analytical solver.

  @article{robotics12040101, abstract = {This manuscript presents an efficient algorithm for solving the inverse kinematics problem of a 6R robot manipulator to be deployed on embedded control hardware. The proposed method utilizes the geometric relationship between the end-effector and the base of the manipulator, resulting in a computationally efficient solution. The approach aims to minimize computational complexity and memory consumption while maintaining the accuracy and real-time performance demonstrated by simulations and verified by experimental results on an embedded system. Furthermore, the manipulator is analyzed in terms of singularities, limits, the workspace, and general solvability. Due to the simplicity of the algorithm, a platform-independent implementation is possible. As a result, the average calculation time is reduced by a factor of five to eight and the average error is decreased by a factor of fifty compared to a powerful analytical solver.}, author = {Anschober, M. and Edlinger, R. and Froschauer, R. and Nüchter, A.}, journal = {Robotics}, keywords = {myown}, number = 4, publisher = {MDPI}, title = {{Inverse Kinematics of an Anthropomorphic 6R Robot Manipulator Based on a Simple Geometric Approach for Embedded Systems}}, volume = 12, year = 2023 }
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  Terrain segmentation for commercial vehicles and working machines. Edlinger, R.; Mitterhuber, U.; Nüchter, A. In Proceedings of the IS\&T International Symposium on Electronic Imaging Science and Technology, of Electronic Imaging, pp. 324–1. Society for Imaging Science and Technology, San Francisco, CA, USA, 2023.
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  In the field of automated working machines, not only is the general trend towards automation in industry, transport and logistics reflected, but new areas of application and markets are also constantly emerging. In this paper we present a pipeline for terrain classification in offroad environments and in the field of "automated maintenance of slopes", which offers potential for solving numerous socio-economic needs. Working tasks can be made more efficient, more ergonomic and, in particular, much safer, because mature, automated vehicles are used. At present, however, such tasks can only be carried out remotely or semi-automatically, under the supervision of a trained specialist. This only partially facilitates the work. The real benefit only comes when the supervising person is released from this task and is able to pursue other work. In addition to the development of a safe integrated system and sensor concept for use in public spaces as a basic prerequisite for vehicles licensed in the future, increased situational awareness of mobile systems through machine learning in order to increase their efficiency and flexibility is also of great importance.

  @inproceedings{EI2023b, abstract = {In the field of automated working machines, not only is the general trend towards automation in industry, transport and logistics reflected, but new areas of application and markets are also constantly emerging. In this paper we present a pipeline for terrain classification in offroad environments and in the field of "automated maintenance of slopes", which offers potential for solving numerous socio-economic needs. Working tasks can be made more efficient, more ergonomic and, in particular, much safer, because mature, automated vehicles are used. At present, however, such tasks can only be carried out remotely or semi-automatically, under the supervision of a trained specialist. This only partially facilitates the work. The real benefit only comes when the supervising person is released from this task and is able to pursue other work. In addition to the development of a safe integrated system and sensor concept for use in public spaces as a basic prerequisite for vehicles licensed in the future, increased situational awareness of mobile systems through machine learning in order to increase their efficiency and flexibility is also of great importance.}, address = {San Francisco, CA, USA}, author = {Edlinger, R. and Mitterhuber, U. and N{\"u}chter, A.}, booktitle = {Proceedings of the IS\&T International Symposium on Electronic Imaging Science and Technology}, keywords = {myown}, month = {01}, pages = {324-1–324-7}, publisher = {Society for Imaging Science and Technology}, series = {Electronic Imaging}, title = {Terrain segmentation for commercial vehicles and working machines}, year = 2023 }
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  LIDAR BASED POSE TRACKING OF AN UNCOOPERATIVE SPACECRAFT USING THE SMOOTHED NORMAL DISTRIBUTION TRANSFORM. Renaut, L.; Frei, H.; Nüchter, A. In Proceedings of the 12th International Conference on Guidance, Navigation & Control Systems (GNC ’23), pp. 1–12. ESA, Sopot, Poland, 2023.
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  Lidar sensors provide precise 3D point cloud measurements, and can be used for pose estima- tion of an uncooperative satellite during space rendezvous. For updating the estimated pose of a the target, iterative closest point (ICP) or one of its variants is usually applied as a tracking method. However, for dense point clouds and space hardware with reduced computing power, the execution time of ICP can become a limiting factor. Normal distribution transform (NDT) is an alternative algorithm for fine point cloud registration, which can be faster than ICP. Yet, NDT can be less robust than ICP due to the discontinuities in its cost function. This work proposes a smoothing method of the NDT map in order to mitigate this robustness problem. In addition, a strategy for correcting motion blur observed with lidar sensors when recording a tumbling target is developed. Experiments at the European Proximity Operations Simulator demonstrate the effi- ciency, precision and robustness of the smoothed NDT algorithm when compared to ICP, as well as the importance of motion blur correction for precise pose estimation.

  @inproceedings{GNC2023, abstract = {Lidar sensors provide precise 3D point cloud measurements, and can be used for pose estima- tion of an uncooperative satellite during space rendezvous. For updating the estimated pose of a the target, iterative closest point (ICP) or one of its variants is usually applied as a tracking method. However, for dense point clouds and space hardware with reduced computing power, the execution time of ICP can become a limiting factor. Normal distribution transform (NDT) is an alternative algorithm for fine point cloud registration, which can be faster than ICP. Yet, NDT can be less robust than ICP due to the discontinuities in its cost function. This work proposes a smoothing method of the NDT map in order to mitigate this robustness problem. In addition, a strategy for correcting motion blur observed with lidar sensors when recording a tumbling target is developed. Experiments at the European Proximity Operations Simulator demonstrate the effi- ciency, precision and robustness of the smoothed NDT algorithm when compared to ICP, as well as the importance of motion blur correction for precise pose estimation.}, address = {Sopot, Poland}, author = {Renaut, L. and Frei, H. and N{\"u}chter, A.}, booktitle = {Proceedings of the 12th International Conference on Guidance, Navigation & Control Systems (GNC '23)}, keywords = {author}, month = {06}, organization = {ESA}, pages = {1–12}, title = {LIDAR BASED POSE TRACKING OF AN UNCOOPERATIVE SPACECRAFT USING THE SMOOTHED NORMAL DISTRIBUTION TRANSFORM}, year = 2023 }
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  Lidar Pose Tracking of a Tumbling Spacecraft Using the Smoothed Normal Distribution Transform. Renaut, L.; Frei, H.; Nüchter, A. In Remote Sensing, 15(9). 2023.
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  Lidar sensors enable precise pose estimation of an uncooperative spacecraft in close range. In this context, the iterative closest point (ICP) is usually employed as a tracking method. However, when the size of the point clouds increases, the required computation time of the ICP can become a limiting factor. The normal distribution transform (NDT) is an alternative algorithm which can be more efficient than the ICP, but suffers from robustness issues. In addition, lidar sensors are also subject to motion blur effects when tracking a spacecraft tumbling with a high angular velocity, leading to a loss of precision in the relative pose estimation. This work introduces a smoothed formulation of the NDT to improve the algorithm’s robustness while maintaining its efficiency. Additionally, two strategies are investigated to mitigate the effects of motion blur. The first consists in un-distorting the point cloud, while the second is a continuous-time formulation of the NDT. Hardware-in-the-loop tests at the European Proximity Operations Simulator demonstrate the capability of the proposed methods to precisely track an uncooperative spacecraft under realistic conditions within tens of milliseconds, even when the spacecraft tumbles with a significant angular rate.

  @article{REMSEN2023, abstract = {Lidar sensors enable precise pose estimation of an uncooperative spacecraft in close range. In this context, the iterative closest point (ICP) is usually employed as a tracking method. However, when the size of the point clouds increases, the required computation time of the ICP can become a limiting factor. The normal distribution transform (NDT) is an alternative algorithm which can be more efficient than the ICP, but suffers from robustness issues. In addition, lidar sensors are also subject to motion blur effects when tracking a spacecraft tumbling with a high angular velocity, leading to a loss of precision in the relative pose estimation. This work introduces a smoothed formulation of the NDT to improve the algorithm’s robustness while maintaining its efficiency. Additionally, two strategies are investigated to mitigate the effects of motion blur. The first consists in un-distorting the point cloud, while the second is a continuous-time formulation of the NDT. Hardware-in-the-loop tests at the European Proximity Operations Simulator demonstrate the capability of the proposed methods to precisely track an uncooperative spacecraft under realistic conditions within tens of milliseconds, even when the spacecraft tumbles with a significant angular rate.}, author = {Renaut, L. and Frei, H. and N{\"u}chter, A.}, journal = {Remote Sensing}, keywords = {author}, number = 9, title = {Lidar Pose Tracking of a Tumbling Spacecraft Using the Smoothed Normal Distribution Transform}, volume = 15, year = 2023 }
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  BED-BPP: Benchmarking dataset for robotic bin packing problems. Kagerer, F.; Beinhofer, M.; Stricker, S.; Nüchter, A. In The International Journal of Robotics Research (IJRR), p. 02783649231193048. 2023.
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  Many algorithms that were developed for solving three-dimensional bin packing problems use generic data for either experiments or evaluation. However, none of these datasets became accepted for benchmarking 3D bin packing algorithms throughout the community. To close this gap, this paper presents the benchmarking dataset for robotic bin packing problems (BED-BPP), which is based on realistic data. We show the variety of the dataset by elaborating an n-gram analysis. Besides, we propose an evaluation function, which contains a stability check that uses rigid body simulation. We demonstrated the application of our dataset on four different approaches, which we integrated in our software environment.

  @article{IJRR2023, abstract = {Many algorithms that were developed for solving three-dimensional bin packing problems use generic data for either experiments or evaluation. However, none of these datasets became accepted for benchmarking 3D bin packing algorithms throughout the community. To close this gap, this paper presents the benchmarking dataset for robotic bin packing problems (BED-BPP), which is based on realistic data. We show the variety of the dataset by elaborating an n-gram analysis. Besides, we propose an evaluation function, which contains a stability check that uses rigid body simulation. We demonstrated the application of our dataset on four different approaches, which we integrated in our software environment.}, author = {Kagerer, F. and Beinhofer, M. and Stricker, S. and N{\"u}chter, A.}, journal = {The International Journal of Robotics Research (IJRR)}, keywords = {author}, month = {08}, pages = {02783649231193048}, title = {BED-BPP: Benchmarking dataset for robotic bin packing problems}, year = 2023 }
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  Online Learning of Neural Surface Light Fields Alongside Real-Time Incremental 3D Reconstruction. Yuan, Y.; Nüchter, A. In IEEE Robotics and Automation Letters (RAL), 8(6), pp. 3843–3850. 2023.
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  Immersive novel view generation is an important technology in the field of graphics and has recently also received attention for operator-based human-robot interaction. However, the involved training is time-consuming, and thus the current test scope is majorly on object capturing. This limits the usage of related models in the robotics community for 3D reconstruction since robots (1) usually only capture a very small range of view directions to surfaces that cause arbitrary predictions on unseen, novel direction, (2) requires real-time algorithms, and (3) work with growing scenes, e.g., in robotic exploration. The letter proposes a novel Neural Surface Light Fields model that copes with the small range of view directions while producing a good result in unseen directions. Exploiting recent encoding techniques, the training of our model is highly efficient. In addition, we design Multiple Asynchronous Neural Agents (MANA), a universal framework to learn each small region in parallel for large-scale growing scenes. Our model learns online the Neural Surface Light Fields (NSLF) aside from real-time 3D reconstruction with a sequential data stream as the shared input. In addition to online training, our model also provides real-time rendering after completing the data stream for visualization. We implement experiments using well-known RGBD indoor datasets, showing the high flexibility to embed our model into real-time 3D reconstruction and demonstrating high-fidelity view synthesis for these scenes.

  @article{RAL2023, abstract = {Immersive novel view generation is an important technology in the field of graphics and has recently also received attention for operator-based human-robot interaction. However, the involved training is time-consuming, and thus the current test scope is majorly on object capturing. This limits the usage of related models in the robotics community for 3D reconstruction since robots (1) usually only capture a very small range of view directions to surfaces that cause arbitrary predictions on unseen, novel direction, (2) requires real-time algorithms, and (3) work with growing scenes, e.g., in robotic exploration. The letter proposes a novel Neural Surface Light Fields model that copes with the small range of view directions while producing a good result in unseen directions. Exploiting recent encoding techniques, the training of our model is highly efficient. In addition, we design Multiple Asynchronous Neural Agents (MANA), a universal framework to learn each small region in parallel for large-scale growing scenes. Our model learns online the Neural Surface Light Fields (NSLF) aside from real-time 3D reconstruction with a sequential data stream as the shared input. In addition to online training, our model also provides real-time rendering after completing the data stream for visualization. We implement experiments using well-known RGBD indoor datasets, showing the high flexibility to embed our model into real-time 3D reconstruction and demonstrating high-fidelity view synthesis for these scenes.}, author = {Yuan, Y. and N{\"u}chter, A.}, journal = {IEEE Robotics and Automation Letters (RAL)}, keywords = {author}, note = {https://jarrome.github.io/NSLF-OL}, number = 6, pages = {3843–3850}, title = {{Online Learning of Neural Surface Light Fields Alongside Real-Time Incremental 3D Reconstruction}}, volume = 8, year = 2023 }
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  Semantic Classification in Uncolored 3D Point Clouds using Multiscale Features. Neumann, M.; Borrmann, D.; Nüchter, A. In Proceedings of the 17th Conference on Intelligent Autonomous Systems (IAS ’22), of Lecture Notes in Networks and Systems, pp. 342–359. Zagreb, Croatia, 2023.
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  While the semantic segmentation of 2D images is already a well-researched field, the assignment of semantic labels to 3D data is lagging behind. This is partly due to the fact that prelabeled training data is only rarely available since not only the training and application of classification methods but also the manual labeling process are much more time-consuming in 3D. This paper focuses on the more classical approach of first calculating features and subsequently applying a classification algorithm. Existing handcrafted feature definitions are enhanced by using multiple selected reductions of the point cloud as approximations. This serves as input to train a well-studied random forest classifier. A comparison to a recently presented deep learning approach, i.e., the Kernel Point Convolution method, reveals that there are well-justified applications for both modern and classical machine learning methods. To enable the smooth conversion of existing 3D scenes to semantically labeled 3D point clouds the tool \emph{Blender2Helios is presented. We show that the therewith generated artificial data is a good choice for training real-world classifiers.

  @inproceedings{IAS2022, abstract = {While the semantic segmentation of 2D images is already a well-researched field, the assignment of semantic labels to 3D data is lagging behind. This is partly due to the fact that prelabeled training data is only rarely available since not only the training and application of classification methods but also the manual labeling process are much more time-consuming in 3D. This paper focuses on the more classical approach of first calculating features and subsequently applying a classification algorithm. Existing handcrafted feature definitions are enhanced by using multiple selected reductions of the point cloud as approximations. This serves as input to train a well-studied random forest classifier. A comparison to a recently presented deep learning approach, i.e., the Kernel Point Convolution method, reveals that there are well-justified applications for both modern and classical machine learning methods. To enable the smooth conversion of existing 3D scenes to semantically labeled 3D point clouds the tool \emph{Blender2Helios} is presented. We show that the therewith generated artificial data is a good choice for training real-world classifiers.}, address = {Zagreb, Croatia}, author = {Neumann, M. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the 17th Conference on Intelligent Autonomous Systems (IAS '22)}, keywords = {myown}, month = {06}, number = 577, pages = {342–359}, series = {Lecture Notes in Networks and Systems}, title = {{Semantic Classification in Uncolored 3D Point Clouds using Multiscale Features}}, year = 2023 }
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  Simultaneous 3D Reconstruction and Vegetation Classification Utilizing a Multispectral Stereo Camera. Vollet, J.; May, S.; Nüchter, A. In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’23), pp. 132–138. 2023.
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  Obstacle detection is crucial for ensuring the safety of autonomous robots and their surroundings in unstructured outdoor environments. Objects with minimal lateral dimensions can pose risks to the robot or serve as important elements in the infrastructure it operates in. Detecting these structures becomes particularly challenging when tall vegetation is present. Distinguishing between soft, traversable objects, such as tufts of grass, and potentially lethal solid obstacles is paramount to a robot’s ability to operate. This paper presents a novel approach that focuses on point cloud generation and vegetation identification to facilitate the safe navigation of autonomous outdoor robots. Our approach uses a single multispectral stereo camera system that employs a novel stereo matching strategy based on binary descriptors for spectrally non-identical image pairs.

  @inproceedings{SSRR2023, abstract = {Obstacle detection is crucial for ensuring the safety of autonomous robots and their surroundings in unstructured outdoor environments. Objects with minimal lateral dimensions can pose risks to the robot or serve as important elements in the infrastructure it operates in. Detecting these structures becomes particularly challenging when tall vegetation is present. Distinguishing between soft, traversable objects, such as tufts of grass, and potentially lethal solid obstacles is paramount to a robot’s ability to operate. This paper presents a novel approach that focuses on point cloud generation and vegetation identification to facilitate the safe navigation of autonomous outdoor robots. Our approach uses a single multispectral stereo camera system that employs a novel stereo matching strategy based on binary descriptors for spectrally non-identical image pairs.}, author = {Vollet, J. and May, S. and N{\"u}chter, A.}, booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '23)}, keywords = {myown}, pages = {132–138}, title = {Simultaneous 3D Reconstruction and Vegetation Classification Utilizing a Multispectral Stereo Camera}, year = 2023 }
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  Smoothed Normal Distribution Transform for Efficient Point Cloud Registration During Space Rendezvous. Renaut, L.; Frei, H.; Nüchter, A. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications -- Volume 5: VISAPP, pp. 919–930. SciTePress, 2023.
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  Next to the iterative closest point (ICP) algorithm, the normal distribution transform (NDT) algorithm is be- coming a second standard for 3D point cloud registration in mobile robotics. Both methods are effective, however they require a sufficiently good initialization to successfully converge. In particular, the discontinuities in the NDT cost function can lead to difficulties when performing the optimization. In addition, when the size of the point clouds increases, performing the registration in real-time becomes challenging. This work in- troduces a Gaussian smoothing technique of the NDT map, which can be done prior to the registration process. A kd-tree adaptation of the typical octree representation of NDT maps is also proposed. The performance of the modified smoothed NDT (S-NDT) algorithm for pairwise scan registration is assessed on two large-scale outdoor datasets, and compared to the performance of a state-of-the-art ICP implementation. S-NDT is around four times faster and as robust as ICP while reaching similar precision. The algorithm is thereafter applied to the problem of LiDAR tracking of a spacecraft in close-range in the context of space rendezvous, demonstrating the performance and applicability to real-time applications.

  @inproceedings{VISAPP2023, abstract = {Next to the iterative closest point (ICP) algorithm, the normal distribution transform (NDT) algorithm is be- coming a second standard for 3D point cloud registration in mobile robotics. Both methods are effective, however they require a sufficiently good initialization to successfully converge. In particular, the discontinuities in the NDT cost function can lead to difficulties when performing the optimization. In addition, when the size of the point clouds increases, performing the registration in real-time becomes challenging. This work in- troduces a Gaussian smoothing technique of the NDT map, which can be done prior to the registration process. A kd-tree adaptation of the typical octree representation of NDT maps is also proposed. The performance of the modified smoothed NDT (S-NDT) algorithm for pairwise scan registration is assessed on two large-scale outdoor datasets, and compared to the performance of a state-of-the-art ICP implementation. S-NDT is around four times faster and as robust as ICP while reaching similar precision. The algorithm is thereafter applied to the problem of LiDAR tracking of a spacecraft in close-range in the context of space rendezvous, demonstrating the performance and applicability to real-time applications.}, author = {Renaut, L. and Frei, H. and Nüchter, A.}, booktitle = {Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications – Volume 5: VISAPP,}, keywords = {author}, organization = {INSTICC}, pages = {919–930}, publisher = {SciTePress}, title = {Smoothed Normal Distribution Transform for Efficient Point Cloud Registration During Space Rendezvous}, year = 2023 }
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  Non-invasive identification of lunar rocks with optical and LiDAR systems. Gmöhling, M.; Köhl, S.; Zevering, J.; Borrmann, D.; Ferrari, S.; Penasa, L.; Pozzobon, R.; Nüchter, A. In Proceedings of the 4th International Planetary Caves Conference 2023 (PCC ’23). Universities Space Research Association, Lunar and Planetary Institute, Haría Municipality, Lanzarote, Spain, 2023.
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  @inproceedings{PCC2023, address = {Haría Municipality, Lanzarote, Spain}, author = {Gm{\"o}hling, M. and K{\"o}hl, S. and Zevering, J. and Borrmann, D. and Ferrari, S. and Penasa, L. and Pozzobon, R. and N{\"u}chter, A.}, booktitle = {Proceedings of the 4th International Planetary Caves Conference 2023 (PCC '23)}, keywords = {author}, month = {05}, organization = {Universities Space Research Association, Lunar and Planetary Institute}, title = {Non-invasive identification of lunar rocks with optical and LiDAR systems}, year = 2023 }
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  3D laser imaging for measuring volumetric shrinkage of horticultural products during drying process. Mollazade, K.; van der Lucht, J.; Jörissen, S.; Nüchter, A. In Computers and Electronics in Agriculture, 207, p. 107749. 2023.
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  The standard method of shrinkage measurement consists of immersion of the product in a fluid in order to calculate the volume changes before and after drying. It is destructive and time-consuming and also is not a practical method to be used in online drying monitoring systems. To date, it has been tried for measuring shrinkage based on passive stereo vision. But no report has been provided so far on the accuracy of this technique and its comparison with conventional method of measuring volumetric shrinkage. On the other hand, because of the small size of dried foodstuff products, it does not seem that the stereo vision to be able to extract high detail point clouds from the surface of objects. Therefore, this research was conducted in order to study the potential use of 3D laser scanning for measurement of the volumetric shrinkage of some horticultural products during drying process. To this end, a calibrated 3D laser imaging system was applied in order to precisely scan the surface of some small size horticultural products (including plum, fig, date, and button mushroom), which take non-symmetric form during the drying process. 2D image of samples was also taken to predict the volumetric shrinkage by various texture analysis methods. Drying was carried out by a convective dryer. The results indicated a significant superiority of 3D laser imaging compared to 2D imaging. The value of correlation coefficient and mean absolute percentage error of multilayer perceptron artificial neural networks models created based on selected spatial features of point clouds in predicting volumetric shrinkage for plum, fig, date, and mushroom was obtained 0.90 and 19.48, 0.95 and 14.25, 0.78 and 23.54, and 0.87 and 9.47, respectively.

  @article{CEAGI2023, abstract = {The standard method of shrinkage measurement consists of immersion of the product in a fluid in order to calculate the volume changes before and after drying. It is destructive and time-consuming and also is not a practical method to be used in online drying monitoring systems. To date, it has been tried for measuring shrinkage based on passive stereo vision. But no report has been provided so far on the accuracy of this technique and its comparison with conventional method of measuring volumetric shrinkage. On the other hand, because of the small size of dried foodstuff products, it does not seem that the stereo vision to be able to extract high detail point clouds from the surface of objects. Therefore, this research was conducted in order to study the potential use of 3D laser scanning for measurement of the volumetric shrinkage of some horticultural products during drying process. To this end, a calibrated 3D laser imaging system was applied in order to precisely scan the surface of some small size horticultural products (including plum, fig, date, and button mushroom), which take non-symmetric form during the drying process. 2D image of samples was also taken to predict the volumetric shrinkage by various texture analysis methods. Drying was carried out by a convective dryer. The results indicated a significant superiority of 3D laser imaging compared to 2D imaging. The value of correlation coefficient and mean absolute percentage error of multilayer perceptron artificial neural networks models created based on selected spatial features of point clouds in predicting volumetric shrinkage for plum, fig, date, and mushroom was obtained 0.90 and 19.48, 0.95 and 14.25, 0.78 and 23.54, and 0.87 and 9.47, respectively.}, author = {Mollazade, K. and van der Lucht, J. and J{\"o}rissen, S. and N{\"u}chter, A.}, journal = {Computers and Electronics in Agriculture}, keywords = {author}, pages = 107749, title = {3D laser imaging for measuring volumetric shrinkage of horticultural products during drying process}, volume = 207, year = 2023 }

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  Advances in Mobile Mapping Technologies. Lehtola, V.; Nüchter, A.; Goulette, F. In of (This book is a printed edition of the Special Issue Advances in Mobile Mapping Technologies that was published in Remote Sensing). MDPI, Basel, Switzerland, 2022.
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  Mobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives. In order to address these topics, we edited the Special Issue Advances in Mobile Mapping Technologies for the Remote Sensing journal. This book contains the published articles of this Special Issue and is aimed at those in academia and industry alike. Specifically, it consists of works introducing a new mobile mapping dataset (‘Paris CARLA 3D’), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We wish to thank all the authors who contributed to this collection.

  @book{MDPISENSORS2022, abstract = {Mobile mapping is applied widely in society, for example, in asset management, fleet management, construction planning, road safety, and maintenance optimization. Yet, further advances in these technologies are called for. Advances can be radical, such as changes to the prevailing paradigms in mobile mapping, or incremental, such as the state-of-the-art mobile mapping methods. With current multi-sensor systems in mobile mapping, laser-scanned data are often registered in point clouds with the aid of global navigation satellite system (GNSS) positioning or simultaneous localization and mapping (SLAM) techniques and then labeled and colored with the aid of machine learning methods and digital camera data. These multi-sensor platforms are beginning to undergo further advancements via the addition of multi-spectral and other sensors and via the development of machine learning techniques used in processing this multi-modal data. Embedded systems and minimalistic system designs are also attracting attention, from both academic and commercial perspectives. In order to address these topics, we edited the Special Issue Advances in Mobile Mapping Technologies for the Remote Sensing journal. This book contains the published articles of this Special Issue and is aimed at those in academia and industry alike. Specifically, it consists of works introducing a new mobile mapping dataset (‘Paris CARLA 3D’), system calibration studies, SLAM topics, and multiple deep learning works for asset detection. We wish to thank all the authors who contributed to this collection.}, address = {Basel, Switzerland}, editor = {Lehtola, V. and N{\"u}chter, A. and Goulette, F.}, keywords = {author}, month = {03}, publisher = {MDPI}, series = {(This book is a printed edition of the Special Issue Advances in Mobile Mapping Technologies that was published in Remote Sensing)}, title = {Advances in Mobile Mapping Technologies}, year = 2022 }
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  Mobile 3D scanning and mapping for freely rotating and vertically descended LiDAR. Arzberger, F.; Zevering, J.; Bredenbeck, A.; Borrmann, D.; Nüchter, A. In Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’22), pp. 122–129. Seville, Spain, 2022.
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  Situational awareness in search and rescue missions is key to successful operations, e.g., in collapsed buildings, underground mine shafts, construction sites, and underwater caves. LiDAR sensors in robotics play an increasingly important role in this context, as do robust and application-specific algorithms for simultaneous localization and mapping (SLAM). In many of these scenarios mapping requires the utilization of a vertically descended scanning system. This work presents a mobile system designed to solve this task, including a SLAM approach for descended LiDAR sensors with small field of view (FoV), which are in uncontrolled rotation. The SLAM approach is based on planar polygon matching and is not limited to the presented scenario. We test the system by lowering it from a crane inside a tall building at a fire-fighter school, applying our offline SLAM approach, and comparing the resulting point clouds of the environment with ground truth maps acquired by a terrestrial laser scanner (TLS). We also compare the SLAM approach to a state-of-the-art approach with respect to runtime and accuracy of the resulting maps. Our solution achieves comparable mapping accuracy at 0.2 of the runtime

  @inproceedings{SSRR2022, abstract = {Situational awareness in search and rescue missions is key to successful operations, e.g., in collapsed buildings, underground mine shafts, construction sites, and underwater caves. LiDAR sensors in robotics play an increasingly important role in this context, as do robust and application-specific algorithms for simultaneous localization and mapping (SLAM). In many of these scenarios mapping requires the utilization of a vertically descended scanning system. This work presents a mobile system designed to solve this task, including a SLAM approach for descended LiDAR sensors with small field of view (FoV), which are in uncontrolled rotation. The SLAM approach is based on planar polygon matching and is not limited to the presented scenario. We test the system by lowering it from a crane inside a tall building at a fire-fighter school, applying our offline SLAM approach, and comparing the resulting point clouds of the environment with ground truth maps acquired by a terrestrial laser scanner (TLS). We also compare the SLAM approach to a state-of-the-art approach with respect to runtime and accuracy of the resulting maps. Our solution achieves comparable mapping accuracy at 0.2 of the runtime}, address = {Seville, Spain}, author = {Arzberger, F. and Zevering, J. and Bredenbeck, A. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '22)}, keywords = {myown}, pages = {122–129}, title = {{M}obile 3D scanning and mapping for freely rotating and vertically descended {LiDAR}}, year = 2022 }
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  Synergetic use of Sentinel-1 and Sentinel-2 data for large-scale Land Use/Land Cover Mapping. Brandmeier, M.; Hell, M.; Cherif, E.; Nüchter, A. In Proceedings of the EGU General Assembly 2022, Poster: Novel Methods and Applications of Satellite and Aerial Imagery. Vienna, Austria \& Online, 2022.
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  @inproceedings{EGU2022, address = {Vienna, Austria \& Online}, author = {Brandmeier, M. and Hell, M. and Cherif, E. and N{\"u}chter, A.}, booktitle = {Proceedings of the EGU General Assembly 2022, Poster: Novel Methods and Applications of Satellite and Aerial Imagery}, keywords = {author}, month = {04}, number = {EGU2022-4300}, title = {{Synergetic use of Sentinel-1 and Sentinel-2 data for large-scale Land Use/Land Cover Mapping}}, year = 2022 }
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  Solving Disaster-response Tasks at a Nuclear Power Plant under Realistic Conditions. Edlinger, R.; Dumberger, S.; Föls, C.; Zouhar, D.; Nüchter, A. In Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC ’22), pp. 104–109. Santa Maria da Feira, Portugal, 2022.
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  Environmental disasters usually trigger devastating damage and, in the worst case, can also cause reactor accidents in nuclear power plants, see Fukushima disaster or other detailed analysis and reports of accident's causes. The correct assessment of natural disasters and the resulting combination with radiological and nuclear accidents, is a major challenge for rescue teams. The conditions under which rescue and recovery operations, as well as exploration and transport tasks, take place are often challenging for emergency responders and involve a certain potential for danger. Serious incidents in the last decades have shown that rescue teams have an urgent need of robotic platforms for fast exploration and scene understanding, especially in scenarios involving radiation. This paper describes the rescue robotic systems used in a test scenario of a nuclear power plant in which the robots must handle sources with real radiation and lessons learned from various application-specific tasks at the EnRicH competition.

  @inproceedings{ICARSC2022_1, abstract = {Environmental disasters usually trigger devastating damage and, in the worst case, can also cause reactor accidents in nuclear power plants, see Fukushima disaster or other detailed analysis and reports of accident's causes. The correct assessment of natural disasters and the resulting combination with radiological and nuclear accidents, is a major challenge for rescue teams. The conditions under which rescue and recovery operations, as well as exploration and transport tasks, take place are often challenging for emergency responders and involve a certain potential for danger. Serious incidents in the last decades have shown that rescue teams have an urgent need of robotic platforms for fast exploration and scene understanding, especially in scenarios involving radiation. This paper describes the rescue robotic systems used in a test scenario of a nuclear power plant in which the robots must handle sources with real radiation and lessons learned from various application-specific tasks at the EnRicH competition.}, address = {Santa Maria da Feira, Portugal}, author = {Edlinger, R. and Dumberger, S. and F{\"o}ls, C. and Zouhar, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC '22)}, keywords = {myown}, month = {04}, pages = {104–109}, title = {{Solving Disaster-response Tasks at a Nuclear Power Plant under Realistic Conditions}}, year = 2022 }
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  Sensor fusion of IMU and GPS for geofencing on an industrial control system for safe mowing in road areas. Dumberger, S.; Edlinger, R.; Bauer, P.; Zauner, M.; Nüchter, A. In Proceedings of the Autrian Robotics Workshop (ARW ’22), M. Brandstötter, G. Steinbauer-Wagner, J. Piater, and L.-M. Faller (eds.), pp. 91–96. Villach, Austria, 2022.
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  The paper presents the implementation of geofenc- ing on a mobile industrial controller for the automation of a mobile carrier vehicle for agricultural use. This system is used to prevent collision with well-known obstacles as well as avoid the accidental run-away of the vehicle under autonomous operation. It describes the mathematical principle used, as well as the additional features needed for a practical implementation on an industrial controller. As it is necessary to ensure the operation under real-world conditions, the paper also handles the data acquisition, pre-filtering and sensor fusion for system. Finally the correct behavior of the system is evaluated with multiple test-cases as well as experimental field tests.

  @inproceedings{ARW2022_2, abstract = {The paper presents the implementation of geofenc- ing on a mobile industrial controller for the automation of a mobile carrier vehicle for agricultural use. This system is used to prevent collision with well-known obstacles as well as avoid the accidental run-away of the vehicle under autonomous operation. It describes the mathematical principle used, as well as the additional features needed for a practical implementation on an industrial controller. As it is necessary to ensure the operation under real-world conditions, the paper also handles the data acquisition, pre-filtering and sensor fusion for system. Finally the correct behavior of the system is evaluated with multiple test-cases as well as experimental field tests.}, address = {Villach, Austria}, author = {Dumberger, S. and Edlinger, R. and Bauer, P. and Zauner, M. and N{\"u}chter, A.}, booktitle = {Proceedings of the Autrian Robotics Workshop (ARW '22)}, editor = {Brandst{\"o}tter, M. and Steinbauer-Wagner, G. and Piater, J. and and L.-M. Faller}, keywords = {myown}, month = {06}, pages = {91–96}, title = {Sensor fusion of IMU and GPS for geofencing on an industrial control system for safe mowing in road areas}, year = 2022 }
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  Advanced Edge Detection of AprilTags for Precise Docking Maneuvers of Mobile Robots. Richter, J.; Bohlig, D.; Nüchter, A.; Schilling, K. In Proceedings of the 6th IFAC Symposium on Telematics Applications (TA ’22), pp. 117–123. Nancy, France, 2022.
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  The development of modules and routines into an existing server-based control station to handle approach and docking maneuvers of mobile systems is the central achievement of this work. Efficient material flow in a digitized factory environment requires that goods are automatically loaded and unloaded onto transport robots. For this purpose, accurate positioning of the robot to a loading station is necessary or to a charging station, to automatically charge the robot’s energy storage. Apart from these applications, robots are furthermore increasingly used for assembly work in production facilities. The possibility of using a transport robot as a mobile montage platform at assembly stations with manipulators is investigated in this work. Crucial for this is the ability to repeatedly acquire a position of sub-centimeter accuracy relative to the station and additionally to transmit the precise final position to the station. The critical component here is the estimation of the mobile system’s pose, which is estimated using camera images of artificial markers attached to the stations. Since the precision of a visual localization strongly depends on the detection accuracy of the markers, an optimization problem is formulated to approximate the edges of the markers using an edge model function and thus determine their corners more precisely. Finally, a planar continuous trajectory planning is implemented to determine the segments of a possible path between any two poses.

  @inproceedings{TA2022_1, abstract = {The development of modules and routines into an existing server-based control station to handle approach and docking maneuvers of mobile systems is the central achievement of this work. Efficient material flow in a digitized factory environment requires that goods are automatically loaded and unloaded onto transport robots. For this purpose, accurate positioning of the robot to a loading station is necessary or to a charging station, to automatically charge the robot’s energy storage. Apart from these applications, robots are furthermore increasingly used for assembly work in production facilities. The possibility of using a transport robot as a mobile montage platform at assembly stations with manipulators is investigated in this work. Crucial for this is the ability to repeatedly acquire a position of sub-centimeter accuracy relative to the station and additionally to transmit the precise final position to the station. The critical component here is the estimation of the mobile system’s pose, which is estimated using camera images of artificial markers attached to the stations. Since the precision of a visual localization strongly depends on the detection accuracy of the markers, an optimization problem is formulated to approximate the edges of the markers using an edge model function and thus determine their corners more precisely. Finally, a planar continuous trajectory planning is implemented to determine the segments of a possible path between any two poses.}, address = {Nancy, France}, author = {Richter, J. and Bohlig, D. and N{\"u}chter, A. and Schilling, K.}, booktitle = {Proceedings of the 6th IFAC Symposium on Telematics Applications (TA '22)}, keywords = {myown}, month = {06}, pages = {117-123}, title = {{Advanced Edge Detection of AprilTags for Precise Docking Maneuvers of Mobile Robots}}, year = 2022 }
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  Radiance values inside lunar caves and lava tubes. Rodeghiero, G.; Pernechele, C.; Munari, M.; Pozzobon, R.; Pajola, M.; Antonio, I. Di; Lucchetti, A.; Massironi, M.; Simioni, E.; Borrmann, D.; Maurelli, F.; Nüchter, A.; Rossi, A. P. In Space Telescopes and Instrumentation 2022: Optical, Infrared, and Millimeter Wave, Vol. 12180, L. E. Coyle, S. Matsuura, M. D. Perrin (eds.), p. 121803B. SPIE, 2022.
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  here is currently a growing interest for the in-situ robotic and human exploration of the Moon’s surface and subsurface. In particular, several mission concepts foresee the exploration of lunar caves and underground structures like e.g. the lava tubes, (i.e. conduit formed by flowing lava from a volcanic vent that moves beneath the hardened surface of a lava flow) and other depressed morphologies such as permanently shadowed craters which could present in situ resources such as water ice. Given the limited onboard resources of these missions and extreme illumination conditions ranging from sunlight to complete darkness, the cameras might be capable of operating without the support of any artificial illumination system. This paper studies the radiance properties of a set of different lunar cave pits as illuminated uniquely by the sunlight for different Sun elevations above the Moon horizon and permanently shadowed craters such as Shackleton’s interior. This is as an endmember for complete darkness of extreme importance because it could be a cold trap for volatiles and a potential future human exploration target. The simulations are carried out using the OpticStudio ray tracing software and a Lambertian scattering model of the cave pit walls. The radiance maps within the caves can be used by the scientific community to estimate the typical Signal to Noise Ratio (SNR) of the required observations with optical cameras deployed on the lunar surface. This is accomplished both for directly illuminated, penumbra and umbra regions of the cave pit. We believe that the proposed investigations are of wide interest for the future missions to the Moon and its robotic and manned exploration.

  @inproceedings{SPIE_2022, abstract = {here is currently a growing interest for the in-situ robotic and human exploration of the Moon’s surface and subsurface. In particular, several mission concepts foresee the exploration of lunar caves and underground structures like e.g. the lava tubes, (i.e. conduit formed by flowing lava from a volcanic vent that moves beneath the hardened surface of a lava flow) and other depressed morphologies such as permanently shadowed craters which could present in situ resources such as water ice. Given the limited onboard resources of these missions and extreme illumination conditions ranging from sunlight to complete darkness, the cameras might be capable of operating without the support of any artificial illumination system. This paper studies the radiance properties of a set of different lunar cave pits as illuminated uniquely by the sunlight for different Sun elevations above the Moon horizon and permanently shadowed craters such as Shackleton’s interior. This is as an endmember for complete darkness of extreme importance because it could be a cold trap for volatiles and a potential future human exploration target. The simulations are carried out using the OpticStudio ray tracing software and a Lambertian scattering model of the cave pit walls. The radiance maps within the caves can be used by the scientific community to estimate the typical Signal to Noise Ratio (SNR) of the required observations with optical cameras deployed on the lunar surface. This is accomplished both for directly illuminated, penumbra and umbra regions of the cave pit. We believe that the proposed investigations are of wide interest for the future missions to the Moon and its robotic and manned exploration.}, author = {Rodeghiero, G. and Pernechele, C. and Munari, M. and Pozzobon, R. and Pajola, M. and Antonio, I. Di and Lucchetti, A. and Massironi, M. and Simioni, E. and Borrmann, D. and Maurelli, F. and N{\"u}chter, A. and Rossi, A. P.}, booktitle = {Space Telescopes and Instrumentation 2022: Optical, Infrared, and Millimeter Wave}, editor = {Coyle, Laura E. and Matsuura, Shuji and Perrin, Marshall D.}, keywords = {Radiance}, organization = {International Society for Optics and Photonics}, pages = {121803B}, publisher = {SPIE}, title = {{Radiance values inside lunar caves and lava tubes}}, volume = 12180, year = 2022 }
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  Pose estimation and mapping based on IMU and LiDAR. Kaltenthaler, J.; Lauterbach, H. A.; Borrmann, D.; Nüchter, A. In Proceedings of the 6th IFAC Symposium on Telematics Applications (TA ’22), pp. 71–76. Nancy, France, 2022.
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  In the field of autonomous motion and mapping, estimating the position and orientiation of a moving body is of high significance. This includes in particular the latest information about acceleration, speed, traveled distance and orientation. A wide range of different technologies exists that can be applied for this purpose. In case the state determination requires the use of inertial sensors only, it is well known that these types of sensors tend to drift with time. This leads to increasing errors in the calculated trajectory, which is unacceptable if precise position information is required such as for mapping. In this paper we present a method which significantly enhances the position estimation of inertial sensors by using a 2D light detection and ranging (LiDAR) sensor.

  @inproceedings{TA2022_2, abstract = {In the field of autonomous motion and mapping, estimating the position and orientiation of a moving body is of high significance. This includes in particular the latest information about acceleration, speed, traveled distance and orientation. A wide range of different technologies exists that can be applied for this purpose. In case the state determination requires the use of inertial sensors only, it is well known that these types of sensors tend to drift with time. This leads to increasing errors in the calculated trajectory, which is unacceptable if precise position information is required such as for mapping. In this paper we present a method which significantly enhances the position estimation of inertial sensors by using a 2D light detection and ranging (LiDAR) sensor.}, address = {Nancy, France}, author = {Kaltenthaler, J. and Lauterbach, H. A. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the 6th IFAC Symposium on Telematics Applications (TA '22)}, keywords = {myown}, month = {06}, pages = {71-76}, title = {{Pose estimation and mapping based on IMU and LiDAR}}, year = 2022 }
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  Modular HRI Approach with reliable and resilient wireless communication for rescue robots and first responders. Edlinger, R.; Anschober, M.; Froschauer, R.; Nüchter, A. In 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN’22). Napoli, Italy, 2022.
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  In this paper, we present a user-selectable con- trol unit to make complex robot systems easier to operate. The robots are primarily used for obtaining information and manipulating dangerous objects or support emergency forces in dealing with crisis situations. Based on hazardous mission scenarios in which mobile robot systems are confronted with complex manipulation and maneuvering tasks (e.g., leakage of contaminants), new methods and concepts in the area of robot decision making, sensor data presentation and control concepts were developed to facilitate the handling and operation of assistance robots. The flexibility of the control concept approach is intended to increase the confidence of the emergency services and to provide intuitive operation of the assistance robots for every user. An intuitive control and stable communication for both control commands and feedback from the robot itself increase trust in the robotic system and its acceptance by the operators. These developments have been investigated in field trials with different types of robots and with network communication constraints.

  @inproceedings{ROMAN2022, abstract = {In this paper, we present a user-selectable con- trol unit to make complex robot systems easier to operate. The robots are primarily used for obtaining information and manipulating dangerous objects or support emergency forces in dealing with crisis situations. Based on hazardous mission scenarios in which mobile robot systems are confronted with complex manipulation and maneuvering tasks (e.g., leakage of contaminants), new methods and concepts in the area of robot decision making, sensor data presentation and control concepts were developed to facilitate the handling and operation of assistance robots. The flexibility of the control concept approach is intended to increase the confidence of the emergency services and to provide intuitive operation of the assistance robots for every user. An intuitive control and stable communication for both control commands and feedback from the robot itself increase trust in the robotic system and its acceptance by the operators. These developments have been investigated in field trials with different types of robots and with network communication constraints.}, address = {Napoli, Italy}, author = {Edlinger, R. and Anschober, M. and Froschauer, R. and N{\"u}chter, A.}, booktitle = {31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN'22)}, keywords = {myown}, month = {08}, title = {{Modular HRI Approach with reliable and resilient wireless communication for rescue robots and first responders}}, year = 2022 }
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  Melt Electrowriting of Poly(dioxanone) Filament Using a Multi-Axis Robot. Luposchainsky, S.; Jörissen, S.; Nüchter, A.; Dalton, P. D. In Macromolecular Materials and Engineering, p. 2200450. 2022.
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  Abstract Excessive thermal degradation is one limitation of scaffold production by melt electrowriting (MEW). This is particularly pertinent when using higher melting point polymers with faster degradation profiles in vivo for tissue engineering applications. This is addressed here by switching from a pneumatic to a filament-based feeding system and demonstrating the processing of a medical polymer, poly(dioxanone) (PDO). Additionally, by replacing the established cartesian printer configuration with a six-axis robotic arm, arbitrary nonplanar surfaces can be used as a fiber collector, as shown here by using a spherical collector. The combination of these techniques allows MEW to be used more broadly in tissue engineering where currently established medical polymers are incompatible with the process, or the geometric shapes of scaffold are to be expanded. It demonstrates the required technology to produce nonplanar scaffolds of PDO in a dome shape with dimensions for a biodegradable corneal implant.

  @article{MACROENG2022, abstract = {Abstract Excessive thermal degradation is one limitation of scaffold production by melt electrowriting (MEW). This is particularly pertinent when using higher melting point polymers with faster degradation profiles in vivo for tissue engineering applications. This is addressed here by switching from a pneumatic to a filament-based feeding system and demonstrating the processing of a medical polymer, poly(dioxanone) (PDO). Additionally, by replacing the established cartesian printer configuration with a six-axis robotic arm, arbitrary nonplanar surfaces can be used as a fiber collector, as shown here by using a spherical collector. The combination of these techniques allows MEW to be used more broadly in tissue engineering where currently established medical polymers are incompatible with the process, or the geometric shapes of scaffold are to be expanded. It demonstrates the required technology to produce nonplanar scaffolds of PDO in a dome shape with dimensions for a biodegradable corneal implant.}, author = {Luposchainsky, S. and Jörissen, S. and N{\"u}chter, A. and Dalton, P. D.}, journal = {Macromolecular Materials and Engineering}, keywords = {author}, month = 10, pages = 2200450, title = {{M}elt {E}lectrowriting of {Poly(dioxanone)} {F}ilament {U}sing a {M}ulti-{A}xis {R}obot}, year = 2022 }
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  Testing AGV mobility control method for MANET coverage optimization using procedural simulation. Sauer, C.; Lyczkowski, E.; Schmidt, M.; Nüchter, A.; Hoßfeld, T. In Computer Communications, 194, pp. 189–201. 2022.
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  In industrial applications continuous wireless connectivity of mobile clients can rarely by guaranteed. Lack of communication negatively impacts the performance of industrial automation systems, e.g. Automated Guided Vehicle (AGV) fleets. Utilizing industrial Mobile Ad-hoc NETworks (MANETs) and an adaptive positioning scheme can reduce the number of disconnections in AGV fleets. Therefore, the performance of the mobile system (e.g. AGV fleet) is improved and factory efficiency increased. In this work procedural simulation is used to examine wireless communication in industrial applications. This method enables the observation of the interaction of mobility control system, network status and robotic system performance independently from a specific environment or scenario. Novel insights on the effectiveness of ad-hoc communication in industrial applications and the correlation of AGV fleet connectedness and AGV fleet transport performance are presented. Additionally, a control method is proposed, which improves the network coverage of an industrial MANET and efficiency of AGV fleets.

  @article{SAUER2022189, abstract = {In industrial applications continuous wireless connectivity of mobile clients can rarely by guaranteed. Lack of communication negatively impacts the performance of industrial automation systems, e.g. Automated Guided Vehicle (AGV) fleets. Utilizing industrial Mobile Ad-hoc NETworks (MANETs) and an adaptive positioning scheme can reduce the number of disconnections in AGV fleets. Therefore, the performance of the mobile system (e.g. AGV fleet) is improved and factory efficiency increased. In this work procedural simulation is used to examine wireless communication in industrial applications. This method enables the observation of the interaction of mobility control system, network status and robotic system performance independently from a specific environment or scenario. Novel insights on the effectiveness of ad-hoc communication in industrial applications and the correlation of AGV fleet connectedness and AGV fleet transport performance are presented. Additionally, a control method is proposed, which improves the network coverage of an industrial MANET and efficiency of AGV fleets.}, author = {Sauer, C. and Lyczkowski, E. and Schmidt, M. and N{\"u}chter, A. and Ho{\ss}feld, T.}, journal = {Computer Communications}, keywords = {myown}, pages = {189–201}, title = {Testing AGV mobility control method for MANET coverage optimization using procedural simulation}, volume = 194, year = 2022 }
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  Aerial 3D Mapping with Continuous Time ICP for Urban Search and Rescue. Lauterbach, H. A.; Nüchter, A. In Autonomous Mobile Mapping Robots, J. B\ce}}dkowski (ed.). IntechOpen, Rijeka, Croatia, 2022.
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  Fast reconnaissance is essential for strategic decisions during the immediate response phase of urban search and rescue missions. Nowadays, UAVs with their advantageous overview perspective are increasingly used for reconnaissance besides manual inspection of the scenario. However, data evaluation is often limited to visual inspection of images or video footage. We present our LiDAR-based aerial 3D map- ping system, providing real-time maps of the environment. UAV-borne laser scans typically offer a reduced field of view. Moreover, UAV trajectories are more flexible and dynamic compared to those of ground vehicles, for which SLAM systems are often designed. We address these challenges by a two-step registration approach based on continuous time ICP. The experiments show that the resulting maps accu- rately represent the environment.

  @incollection{INTECH22B, abstract = {Fast reconnaissance is essential for strategic decisions during the immediate response phase of urban search and rescue missions. Nowadays, UAVs with their advantageous overview perspective are increasingly used for reconnaissance besides manual inspection of the scenario. However, data evaluation is often limited to visual inspection of images or video footage. We present our LiDAR-based aerial 3D map- ping system, providing real-time maps of the environment. UAV-borne laser scans typically offer a reduced field of view. Moreover, UAV trajectories are more flexible and dynamic compared to those of ground vehicles, for which SLAM systems are often designed. We address these challenges by a two-step registration approach based on continuous time ICP. The experiments show that the resulting maps accu- rately represent the environment.}, address = {Rijeka, Croatia}, author = {Lauterbach, H. A. and N{\"u}chter, A.}, booktitle = {{A}utonomous {M}obile {M}apping {R}obots}, chapter = 6, editor = {B{\c{e}}dkowski, Janusz}, keywords = {myown}, publisher = {IntechOpen}, title = {{A}erial {3D} {M}apping with {C}ontinuous {T}ime {ICP} for {U}rban {S}earch and {R}escue}, year = 2022 }
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  Door Pose Estimation and Robot Positioning for Autonomous Door Opening. Mitterhuber, U.; Edlinger, R.; Froschauer, R.; Nüchter, A. In Proceedings of the Autrian Robotics Workshop (ARW ’22), M. Brandstötter, G. Steinbauer-Wagner, J. Piater, and L.-M. Faller (eds.), pp. 36–41. Villach, Austria, 2022.
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  For autonomous robots to deliver value in human centered environments, they must be able to autonomously open doors. For doing so, they have to overcome multiple challenges, one of which is, to estimate the desired door’s orientation and position. The information if the door handle is on the left or right side of the door must also be obtained. In this work, a novel method, solving the stated problems is proposed. It’s perception is based on a sensor fusion of a monocular camera based state-of-the-art deep learning object detection algorithm with a 2D laser scan and subsequent line estimation. Additionally, a differential drive controller, using the advancement of continuous goal pose updating, is proposed. During real-world experimentation with a differential drive robot, the implemented system was able to position the robot in front of a door every time with sufficient accuracy and is thus found to solve the stated problem successfully.

  @inproceedings{ARW2022_1, abstract = {For autonomous robots to deliver value in human centered environments, they must be able to autonomously open doors. For doing so, they have to overcome multiple challenges, one of which is, to estimate the desired door’s orientation and position. The information if the door handle is on the left or right side of the door must also be obtained. In this work, a novel method, solving the stated problems is proposed. It’s perception is based on a sensor fusion of a monocular camera based state-of-the-art deep learning object detection algorithm with a 2D laser scan and subsequent line estimation. Additionally, a differential drive controller, using the advancement of continuous goal pose updating, is proposed. During real-world experimentation with a differential drive robot, the implemented system was able to position the robot in front of a door every time with sufficient accuracy and is thus found to solve the stated problem successfully.}, address = {Villach, Austria}, author = {Mitterhuber, U. and Edlinger, R. and Froschauer, R. and N{\"u}chter, A.}, booktitle = {Proceedings of the Autrian Robotics Workshop (ARW '22)}, editor = {Brandst{\"o}tter, M. and Steinbauer-Wagner, G. and Piater, J. and and L.-M. Faller}, keywords = {myown}, month = {06}, pages = {36–41}, title = {Door Pose Estimation and Robot Positioning for Autonomous Door Opening}, year = 2022 }
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  Dynamic Point Cloud Compression Based on Projections, Surface Reconstruction and Video Compression. Dumic, E.; Bjelopera, A.; Nüchter, A. In Sensors, 22(1). 2022.
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  In this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for obtained geometry and texture maps. Texture maps have been compressed after creating Voronoi diagrams. Used video compression is specific for geometry (FFV1) and texture (H.265/HEVC). Decompressed point clouds are reconstructed using a Poisson surface reconstruction algorithm. Comparison with the original point clouds was performed using point-to-point and point-to-plane measures. Comprehensive experiments show better performance for some projection maps: cylindrical, Miller and Mercator projections.

  @article{MDPI2022, abstract = {In this paper we will present a new dynamic point cloud compression based on different projection types and bit depth, combined with the surface reconstruction algorithm and video compression for obtained geometry and texture maps. Texture maps have been compressed after creating Voronoi diagrams. Used video compression is specific for geometry (FFV1) and texture (H.265/HEVC). Decompressed point clouds are reconstructed using a Poisson surface reconstruction algorithm. Comparison with the original point clouds was performed using point-to-point and point-to-plane measures. Comprehensive experiments show better performance for some projection maps: cylindrical, Miller and Mercator projections.}, author = {Dumic, E. and Bjelopera, A. and N{\"u}chter, A.}, journal = {Sensors}, keywords = {sys:relevantfor:uniwue_cs7}, number = 1, title = {{Dynamic Point Cloud Compression Based on Projections, Surface Reconstruction and Video Compression}}, volume = 22, year = 2022 }
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  KINECT BACKPACK FOR RAPID MOBILE INDOOR MAPPING. Bleier, M.; van der Lucht, J.; Nüchter, A. In Proceedings of the ISPRS Congress 2022, of ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 121–127. Nice, France, 2022.
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  In recent years, 3D surveying using mobile mapping has become increasingly popular. Handheld or backpack mounted systems resulted in new uses and applications because they enable fast data acquisition in areas that are difficult to access. Many of these applications do not require high-precision measurement, but they often involve highly complex environments. In this paper, we present a mobile mapping backpack based on four Microsoft Kinect RGB-D sensors and an Intel T265 tracking camera. The data processing takes place in three steps. Starting with a first trajectory and map created using visual-inertial odometry, which is subsequently optimized by means of a continuous-time ICP. Finally, the trajectory is further improved by a continuous-time SLAM approach. In this work, a data set was recorded and analyzed in a bunker facility with the system carried at a walking speed of approximately 0.7 meters per second. For the evaluation, these data are compared with a reference data set, recorded with a Riegl VZ-400 laser scanner.

  @inproceedings{ISPRSCongress2022, abstract = {In recent years, 3D surveying using mobile mapping has become increasingly popular. Handheld or backpack mounted systems resulted in new uses and applications because they enable fast data acquisition in areas that are difficult to access. Many of these applications do not require high-precision measurement, but they often involve highly complex environments. In this paper, we present a mobile mapping backpack based on four Microsoft Kinect RGB-D sensors and an Intel T265 tracking camera. The data processing takes place in three steps. Starting with a first trajectory and map created using visual-inertial odometry, which is subsequently optimized by means of a continuous-time ICP. Finally, the trajectory is further improved by a continuous-time SLAM approach. In this work, a data set was recorded and analyzed in a bunker facility with the system carried at a walking speed of approximately 0.7 meters per second. For the evaluation, these data are compared with a reference data set, recorded with a Riegl VZ-400 laser scanner.}, address = {Nice, France}, author = {Bleier, M. and van der Lucht, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the ISPRS Congress 2022}, keywords = {sys:relevantfor:uniwue_cs7}, number = {V-1-2022}, pages = {121–127}, series = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, title = {{KINECT BACKPACK FOR RAPID MOBILE INDOOR MAPPING}}, year = 2022 }
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  Indirect Point Cloud Registration: Aligning Distance Fields Using a Pseudo Third Point Set. Yuan, Y.; Nüchter, A. In IEEE Robotics and Automation Letters (RAL), 7(3), pp. 7075–7082. 2022.
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  In recent years, implicit functions have drawn attention in the field of 3D reconstruction and have successfully been applied with Deep Learning. However, for incremental reconstruction, implicit function-based registrations have been rarely explored. Inspired by the high precision of deep learning global feature registration, we propose to combine this with distance fields. We generalize the algorithm to a non-Deep Learning setting while retaining the accuracy. Our algorithm is more accurate than conventional models while, without any training, it achieves a competitive performance and faster speed, compared to Deep Learning-based registration models. The implementation is available on github for the research community.

  @article{RAL2022_1, abstract = {In recent years, implicit functions have drawn attention in the field of 3D reconstruction and have successfully been applied with Deep Learning. However, for incremental reconstruction, implicit function-based registrations have been rarely explored. Inspired by the high precision of deep learning global feature registration, we propose to combine this with distance fields. We generalize the algorithm to a non-Deep Learning setting while retaining the accuracy. Our algorithm is more accurate than conventional models while, without any training, it achieves a competitive performance and faster speed, compared to Deep Learning-based registration models. The implementation is available on github for the research community.}, author = {Yuan, Y. and N{\"u}chter, A.}, journal = {IEEE Robotics and Automation Letters (RAL)}, keywords = {sys:relevantfor:uniwue_cs7}, number = 3, pages = {7075–7082}, title = {{Indirect Point Cloud Registration: Aligning Distance Fields Using a Pseudo Third Point Set}}, volume = 7, year = 2022 }
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  Finding and Following Optimal Trajectories for an Overactuated Floating Robotic Platform. Bredenbeck, A.; Vyas, S.; Suter, W.; Zwick, M.; Borrmann, D.; Olivares-Mendez, M.; Nüchter, A. In 16th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA ’22). ESA, Noordwijk, Netherlands, 2022.
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  The recent increase in yearly spacecraft launches and the high number of planned launches have raised questions about maintaining accessibility to space for all interested parties. A key to sustaining the future of space-flight is the ability to service malfunctioning - and actively remove dysfunctional spacecraft from orbit. Robotic platforms that autonomously perform these tasks are a topic of ongoing research and thus must undergo thorough testing before launch. For representative system-level testing, the European Space Agency (ESA) uses, among other things, the Orbital Robotics and GNC Lab (ORGL), a flat-floor facility where air-bearing based platforms exhibit free-floating behavior in three Degrees of Freedom (DoF). This work introduces a representative simulation of a free-floating platform in the testing environment and a software framework for controller development. Finally, this work proposes a controller within that framework for finding and following optimal trajectories between arbitrary states, which is evaluated in simulation and reality.

  @inproceedings{ASTRA2022, abstract = {The recent increase in yearly spacecraft launches and the high number of planned launches have raised questions about maintaining accessibility to space for all interested parties. A key to sustaining the future of space-flight is the ability to service malfunctioning - and actively remove dysfunctional spacecraft from orbit. Robotic platforms that autonomously perform these tasks are a topic of ongoing research and thus must undergo thorough testing before launch. For representative system-level testing, the European Space Agency (ESA) uses, among other things, the Orbital Robotics and GNC Lab (ORGL), a flat-floor facility where air-bearing based platforms exhibit free-floating behavior in three Degrees of Freedom (DoF). This work introduces a representative simulation of a free-floating platform in the testing environment and a software framework for controller development. Finally, this work proposes a controller within that framework for finding and following optimal trajectories between arbitrary states, which is evaluated in simulation and reality.}, address = {Noordwijk, Netherlands}, author = {Bredenbeck, A. and Vyas, S. and Suter, W. and Zwick, M. and Borrmann, D. and Olivares-Mendez, M. and N{\"u}chter, A.}, booktitle = {16th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA '22)}, keywords = {sys:relevantfor:uniwue_cs7}, month = {06}, publisher = {ESA}, title = {{Finding and Following Optimal Trajectories for an Overactuated Floating Robotic Platform}}, year = 2022 }
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  Field Experiments with an Automated Utility Platform for Transportation and Work Processes. Edlinger, R.; Dumberger, S.; Froschauer, R.; Pointner, W.; Zeilinger, M.; Nüchter, A. In Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC ’22), pp. 21–26. Santa Maria da Feira, Portugal, 2022.
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  The automation of transport and work tasks in various application domains continues to be a major challenge. The proposed paper presents key technologies within a process from sensing to reasoning and includes: (i) understanding the scene and its relations through new approaches in object classification and pose estimation based on machine learning, as well as methods for reliable detection of objects and object features; (ii) reliable and safe outdoor localization and mapping based on multi-modal approaches and innovative camera-based methods. The fusion of different sensor data is used for reliable obstacle detection and collision avoidance. The investigation of suitable system architectures, data processing platforms and communication mechanisms taking into account safety requirements is a prerequisite for the operation in a safety-critical environment. The paper provides a proof of concept for an automated platform to demonstrate and evaluate application scenario provided by the Linz Airport in the form of an automated transport process for air freight between a terminal and the aircraft.

  @inproceedings{ICARSC2022_2, abstract = {The automation of transport and work tasks in various application domains continues to be a major challenge. The proposed paper presents key technologies within a process from sensing to reasoning and includes: (i) understanding the scene and its relations through new approaches in object classification and pose estimation based on machine learning, as well as methods for reliable detection of objects and object features; (ii) reliable and safe outdoor localization and mapping based on multi-modal approaches and innovative camera-based methods. The fusion of different sensor data is used for reliable obstacle detection and collision avoidance. The investigation of suitable system architectures, data processing platforms and communication mechanisms taking into account safety requirements is a prerequisite for the operation in a safety-critical environment. The paper provides a proof of concept for an automated platform to demonstrate and evaluate application scenario provided by the Linz Airport in the form of an automated transport process for air freight between a terminal and the aircraft.}, address = {Santa Maria da Feira, Portugal}, author = {Edlinger, R. and Dumberger, S. and Froschauer, R. and Pointner, W. and Zeilinger, M. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC '22)}, keywords = {myown}, month = {04}, pages = {21–26}, title = {{Field Experiments with an Automated Utility Platform for Transportation and Work Processes}}, year = 2022 }
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  Terrain prediction with a low-cost LIDAR sensor for mobile robots. Edlinger, R.; Nüchter, A. In Proceedings of LowCost3D 2022, of ISPRS Int. Archives Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLVIII-2/W1-2022, pp. 81–86. Würzburg, Germany, 2022.
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  Terrain modelling influences various aspects of mobile robot navigation. The ability to explore in rough terrain and to recognise ground conditions are essential to perform different activities efficiently, safely and satisfactorily. For this reason, intelligent vehicles and robotic systems need cognitive capabilities to understand the terrain and derive information from it. The information is mostly acquired and processed by very high resolution 3D-cameras and LiDAR sensors which provide full 360-degree environmental view to deliver accurate 3D data. The aim of this paper is to find out whether a low-cost sensor variant can measure sufficient and significant data from the terrain in order to modify the navigation behaviour and provide the correct control commands. In this paper we describe a low-cost sensor with Infrared Time-of-Flight (ToF) technology and 64 pixel depth image. Furthermore, different experiments on the detection of the sensor were conducted and with appropriate filters and signal processing algorithms the environmental perception could be significantly improved. In summary, our results provide both evidence and guidelines for the use of the selected sensor in environmental perception to improve local obstacle detection and terrain modelling, which we believe will lead to a very cost-effective improvement in competence and situational awareness.

  @inproceedings{LC2022, abstract = {Terrain modelling influences various aspects of mobile robot navigation. The ability to explore in rough terrain and to recognise ground conditions are essential to perform different activities efficiently, safely and satisfactorily. For this reason, intelligent vehicles and robotic systems need cognitive capabilities to understand the terrain and derive information from it. The information is mostly acquired and processed by very high resolution 3D-cameras and LiDAR sensors which provide full 360-degree environmental view to deliver accurate 3D data. The aim of this paper is to find out whether a low-cost sensor variant can measure sufficient and significant data from the terrain in order to modify the navigation behaviour and provide the correct control commands. In this paper we describe a low-cost sensor with Infrared Time-of-Flight (ToF) technology and 64 pixel depth image. Furthermore, different experiments on the detection of the sensor were conducted and with appropriate filters and signal processing algorithms the environmental perception could be significantly improved. In summary, our results provide both evidence and guidelines for the use of the selected sensor in environmental perception to improve local obstacle detection and terrain modelling, which we believe will lead to a very cost-effective improvement in competence and situational awareness.}, address = {W{\"u}rzburg, Germany}, author = {Edlinger, R. and N{\"u}chter, A.}, booktitle = {Proceedings of LowCost3D 2022}, keywords = {author}, month = 12, pages = {81–86}, series = {ISPRS Int. Archives Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLVIII-2/W1-2022}, title = {{T}errain prediction with a low-cost {LIDAR} sensor for mobile robots}, year = 2022 }
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  Entwicklung einer randomisierten Hough-Transformation zur Zylinderdetektion in Laserscans. Menninger, S.; Bleier, and M.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2022, Jade Hochschule, pp. 260–267. Wichmann, 2022.
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  Neben Ebenen sind Zylinder eine der am häufigsten auftretenden grundlegenden Formen im industriellen Bereich, da sie als geometrische Primitive für Rohrleitungen, Gerüste und dergleichen dienen. Eine schnelle, effiziente und robuste Methode zur Detektion von Zylindern in Punktwolken ist somit essenziell, um die manuellen Schritte bei der Modellerzeugung zu minimieren. Auch wenn es möglich ist, mithilfe einer 5D Hough-Transformation Zylinder zu detektieren, so ist dieser Ansatz doch sehr komplex und zeitintensiv. Aus diesem Grund ist diese Methode auf großen Punktwolken nicht direkt anwendbar. Eine Verringerung der Komplexität kann durch einen sequenziellen zwei Schritt Ansatz ermöglicht werden. Der erste Schritt findet mithilfe einer 2D-Hough-Transformation eine starke Hypothese für die Zylinderachsenorientierung, während sich der Zweite mit der Suche des Radius und der Zylinderposition im dreidimensionalen Raum beschäftigt. Die vorliegende Arbeit stellt eine Randomized Hough-Transformation (RHT) basierte Implementierung vor, die sich damit beschäftigt, möglichst effizient Zylinder und Teilzylinder bis hin zu Halbzylindern automatisch zu detektieren. Mithilfe Simulations- sowie Echtdaten werden die Resultate anschließend verifiziert und bewertet.

  @inproceedings{3DTAGE2022_1, abstract = {Neben Ebenen sind Zylinder eine der am häufigsten auftretenden grundlegenden Formen im industriellen Bereich, da sie als geometrische Primitive für Rohrleitungen, Gerüste und dergleichen dienen. Eine schnelle, effiziente und robuste Methode zur Detektion von Zylindern in Punktwolken ist somit essenziell, um die manuellen Schritte bei der Modellerzeugung zu minimieren. Auch wenn es möglich ist, mithilfe einer 5D Hough-Transformation Zylinder zu detektieren, so ist dieser Ansatz doch sehr komplex und zeitintensiv. Aus diesem Grund ist diese Methode auf großen Punktwolken nicht direkt anwendbar. Eine Verringerung der Komplexität kann durch einen sequenziellen zwei Schritt Ansatz ermöglicht werden. Der erste Schritt findet mithilfe einer 2D-Hough-Transformation eine starke Hypothese für die Zylinderachsenorientierung, während sich der Zweite mit der Suche des Radius und der Zylinderposition im dreidimensionalen Raum beschäftigt. Die vorliegende Arbeit stellt eine Randomized Hough-Transformation (RHT) basierte Implementierung vor, die sich damit beschäftigt, möglichst effizient Zylinder und Teilzylinder bis hin zu Halbzylindern automatisch zu detektieren. Mithilfe Simulations- sowie Echtdaten werden die Resultate anschließend verifiziert und bewertet.}, author = {Menninger, S. and and M. Bleier and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2022, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {260–267}, publisher = {Wichmann}, title = {{Entwicklung einer randomisierten Hough-Transformation zur Zylinderdetektion in Laserscans}}, year = 2022 }
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  An Algorithm for the SE(3)-Transformation on Neural Implicit Maps for Remapping Functions. Yuan, Y.; Nüchter, A. In IEEE Robotics and Automation Letters (RAL), 7(3), pp. 7763–7770. 2022.
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  Implicit representations are widely used for object reconstruction due their efficiency and flexibility. In 2021, a novel structure named neural implicit map has been invented for incremental reconstruction. A neural implicit map alleviates the problem of inefficient memory cost of previous online 3D dense reconstruction while producing better quality. However, the neural implicit map suffers the limitations that it does not support remapping as the frames of scans are encoded into a deep prior after generating the neural implicit map. This means, neither this generation process is invertible, nor a deep prior is transformable. The non-remappable property makes it not possible to apply loop-closure techniques. We present an implicit-map based transformation algorithm to fill this gap. As our implicit-map is transformable, our model supports remapping for this special map of latent features. Experiments show that our remapping module is capable to well-transform neural implicit maps to new poses. Embedded into a SLAM framework, our mapping model is able to tackle remapping of loop-closures and demonstrates high-quality surface reconstruction. Our implementation is available at github (https://github.com/Jarrome/IMT_Mapping) for the research community.

  @article{RAL2022_2, abstract = {Implicit representations are widely used for object reconstruction due their efficiency and flexibility. In 2021, a novel structure named neural implicit map has been invented for incremental reconstruction. A neural implicit map alleviates the problem of inefficient memory cost of previous online 3D dense reconstruction while producing better quality. However, the neural implicit map suffers the limitations that it does not support remapping as the frames of scans are encoded into a deep prior after generating the neural implicit map. This means, neither this generation process is invertible, nor a deep prior is transformable. The non-remappable property makes it not possible to apply loop-closure techniques. We present an implicit-map based transformation algorithm to fill this gap. As our implicit-map is transformable, our model supports remapping for this special map of latent features. Experiments show that our remapping module is capable to well-transform neural implicit maps to new poses. Embedded into a SLAM framework, our mapping model is able to tackle remapping of loop-closures and demonstrates high-quality surface reconstruction. Our implementation is available at github (https://github.com/Jarrome/IMT_Mapping) for the research community.}, author = {Yuan, Y. and N{\"u}chter, A.}, journal = {IEEE Robotics and Automation Letters (RAL)}, keywords = {myown}, month = {07}, number = 3, pages = {7763–7770}, title = {{An Algorithm for the SE(3)-Transformation on Neural Implicit Maps for Remapping Functions}}, volume = 7, year = 2022 }
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  An approach for monitoring temperature on fruit surface by means of thermal point cloud. Tsoulias, N.; Jörissen, S.; Nüchter, A. In MethodsX, 9, p. 101712. 2022.
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  Heat and excessive solar radiation can produce abiotic stresses during apple maturation, resulting fruit quality. Therefore, the monitoring of temperature on fruit surface (FST) over the growing period can allow to identify thresholds, above of which several physiological disorders such as sunburn may occur in apple. The current approaches neglect spatial variation of FST and have reduced repeatability, resulting in unreliable predictions. In this study, LiDAR laser scanning and thermal imaging were employed to detect the temperature on fruit surface by means of 3D point cloud. A process for calibrating the two sensors based on an active board target and producing a 3D thermal point cloud was suggested. After calibration, the sensor system was utilised to scan the fruit trees, while temperature values assigned in the corresponding 3D point cloud were based on the extrinsic calibration. Whereas a fruit detection algorithm was performed in order to segment the FST from each apple.•The approach allows the calibration of LiDAR laser scanner with thermal camera in order to produce a 3D thermal point cloud.•The method can be applied in apple trees for segmenting FST in 3D. Whereas the approach can be utilised to predict several physiological disorders including sunburn on fruit surface.

  @article{METHODSX2022, abstract = {Heat and excessive solar radiation can produce abiotic stresses during apple maturation, resulting fruit quality. Therefore, the monitoring of temperature on fruit surface (FST) over the growing period can allow to identify thresholds, above of which several physiological disorders such as sunburn may occur in apple. The current approaches neglect spatial variation of FST and have reduced repeatability, resulting in unreliable predictions. In this study, LiDAR laser scanning and thermal imaging were employed to detect the temperature on fruit surface by means of 3D point cloud. A process for calibrating the two sensors based on an active board target and producing a 3D thermal point cloud was suggested. After calibration, the sensor system was utilised to scan the fruit trees, while temperature values assigned in the corresponding 3D point cloud were based on the extrinsic calibration. Whereas a fruit detection algorithm was performed in order to segment the FST from each apple.•The approach allows the calibration of LiDAR laser scanner with thermal camera in order to produce a 3D thermal point cloud.•The method can be applied in apple trees for segmenting FST in 3D. Whereas the approach can be utilised to predict several physiological disorders including sunburn on fruit surface.}, author = {Tsoulias, N. and Jörissen, S. and N{\"u}chter, A.}, journal = {MethodsX}, keywords = {author}, pages = 101712, title = {An approach for monitoring temperature on fruit surface by means of thermal point cloud}, volume = 9, year = 2022 }
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  The concept of a maximal network plan to enhance automated decision making in production steering. Larek, R.; Wagner, J. C.; Grendel, H.; Nüchter, A. In Production Engineering. 2022.
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  Digitalization is a major driver of competitiveness in industry. Especially, automated scheduling systems are broadly available to deal with production steering in complex production systems. Their underlying concept is the network plan to describe the logical relation between different production steps for the completion of a production process. The network plan, however, is limited to contain only one standard process and allows therefore basically only the automated variation of execution time of each step within the given logical sequence. This is sufficient as long as the production process and the boundary conditions, such as resource availability, are stable to a certain degree. This work introduces an enhancement of the concept of the network plan, the Maximal Network Plan, that is designed to automatically cope with disruptions. It stores additional alternative sequences, weighted according to their priority in comparison to the standard process. Therefore, a numerical decision making is possible in terms of also varying the order of production tasks to achieve a maximum performance for the overall process. Instead of waiting for a disruption in the standard process to be solved, an alternative sequence will be proposed to increase overall progress by circumventing the blocked step. This concept has been developed and tested for complex assembly tasks, such as the production of air- and spacecraft structures and systems. In conjunction with the use of mobile computing devices instead of paper-based work order documents it allows a very fast and dynamic production steering, also in the case of substantial disruptions in the standard process.

  @article{ProdEng_2022, abstract = {Digitalization is a major driver of competitiveness in industry. Especially, automated scheduling systems are broadly available to deal with production steering in complex production systems. Their underlying concept is the network plan to describe the logical relation between different production steps for the completion of a production process. The network plan, however, is limited to contain only one standard process and allows therefore basically only the automated variation of execution time of each step within the given logical sequence. This is sufficient as long as the production process and the boundary conditions, such as resource availability, are stable to a certain degree. This work introduces an enhancement of the concept of the network plan, the Maximal Network Plan, that is designed to automatically cope with disruptions. It stores additional alternative sequences, weighted according to their priority in comparison to the standard process. Therefore, a numerical decision making is possible in terms of also varying the order of production tasks to achieve a maximum performance for the overall process. Instead of waiting for a disruption in the standard process to be solved, an alternative sequence will be proposed to increase overall progress by circumventing the blocked step. This concept has been developed and tested for complex assembly tasks, such as the production of air- and spacecraft structures and systems. In conjunction with the use of mobile computing devices instead of paper-based work order documents it allows a very fast and dynamic production steering, also in the case of substantial disruptions in the standard process.}, author = {Larek, R. and Wagner, J. C. and Grendel, H. and N{\"u}chter, A.}, journal = {Production Engineering}, keywords = {myown}, month = {07}, title = {The concept of a maximal network plan to enhance automated decision making in production steering}, year = 2022 }
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  AI supported Multi-Functional Gripping System for Dexterous Manipulation Tasks. Edlinger, R.; Föls, C.; Mitterhuber, U.; Nüchter, A. In Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’22), pp. 145–152. Seville, Spain, 2022.
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  Dexterous mobile manipulators that are capable of performing a wide array of tasks are essential for unstructured human-centered environments. Especially in rescue scenarios where time and resources are limited, a gripping system should be as versatile but at the same time as efficient as possible. In addition, situational awareness in accidents and impaired visibility is essential for safely performing missions or automating behaviors, and thus supporting operators. The main contribution of this work is a multi-functional gripping system with technologies and methods for manipulation in rescue and recovery operations as well as for handling hazardous materials. The gripping system is supplemented by an RGB and thermal camera and object detection algorithms, which run in real-time on an embedded device for robust recognition in harsh and dynamic environments. The proposed multi-functional gripping system has been thoroughly evaluated and tested in laboratory experiments and real field facilities.

  @inproceedings{SSRR2022_2, abstract = {Dexterous mobile manipulators that are capable of performing a wide array of tasks are essential for unstructured human-centered environments. Especially in rescue scenarios where time and resources are limited, a gripping system should be as versatile but at the same time as efficient as possible. In addition, situational awareness in accidents and impaired visibility is essential for safely performing missions or automating behaviors, and thus supporting operators. The main contribution of this work is a multi-functional gripping system with technologies and methods for manipulation in rescue and recovery operations as well as for handling hazardous materials. The gripping system is supplemented by an RGB and thermal camera and object detection algorithms, which run in real-time on an embedded device for robust recognition in harsh and dynamic environments. The proposed multi-functional gripping system has been thoroughly evaluated and tested in laboratory experiments and real field facilities.}, address = {Seville, Spain}, author = {Edlinger, R. and F{\"o}ls, C. and Mitterhuber, U. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '22)}, keywords = {myown}, month = 11, pages = {145–152}, title = {{AI supported Multi-Functional Gripping System for Dexterous Manipulation Tasks}}, year = 2022 }
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  The concept of rod-driven locomotion for spherical lunar exploration robots. Zevering, J.; Borrmann, D.; Bredenbeck, A.; Nüchter, A. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’22), pp. 5656–5663. Kyoto, Japan, 2022.
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  A spherical robotic probe has several advantages in rough environments and has therefore raised interest for application in planetary exploration. A sphere is well-suited to protect high-sensitive payloads, however, the locomotion system for planetary surfaces raises several challenges. This paper presents a novel locomotion system consisting of linear actuators which are usable in a multi-functional fashion. Apart from pushing and bringing leverage for locomotion the extendable rods enable a tripod mode for improved sensing. The developed solutions offer a mathematical-physical system description, simple algorithms for the control of locomotion and balancing as well as general calculations for determining the maximum achievable performance parameters of such a robot. The first built prototype shows the basic suitability of the system and reveals directions for further research.

  @inproceedings{IROS2022_1, abstract = {A spherical robotic probe has several advantages in rough environments and has therefore raised interest for application in planetary exploration. A sphere is well-suited to protect high-sensitive payloads, however, the locomotion system for planetary surfaces raises several challenges. This paper presents a novel locomotion system consisting of linear actuators which are usable in a multi-functional fashion. Apart from pushing and bringing leverage for locomotion the extendable rods enable a tripod mode for improved sensing. The developed solutions offer a mathematical-physical system description, simple algorithms for the control of locomotion and balancing as well as general calculations for determining the maximum achievable performance parameters of such a robot. The first built prototype shows the basic suitability of the system and reveals directions for further research.}, address = {Kyoto, Japan}, author = {Zevering, J. and Borrmann, D. and Bredenbeck, A. and N{\"u}chter, A.}, booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '22)}, keywords = {myown}, month = 10, pages = {5656–5663}, title = {{The concept of rod-driven locomotion for spherical lunar exploration robots}}, year = 2022 }
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  WIP: Real-world 3D models derived from mobile mapping for ray launching based propagation loss modeling. Wahl, T.; Borrmann, D.; Bleier, M.; Nüchter, A.; Wiemann, T.; Hänel, T.; Aschenbruck, N. In Proceedings of the 23rd IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM ’22), pp. 1–4. Belfast, UK, 2022.
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  This work in progress paper presents an automated approach for network coverage prediction in real-world environments by combining mobile mapping, 3D mesh generation, and a ray launching based network simulator. We identify the challenges and demonstrate the functionality of such a pipeline. We preview an empirical evaluation in a realistic real-world environment.

  @inproceedings{WOWMOM2022, abstract = {This work in progress paper presents an automated approach for network coverage prediction in real-world environments by combining mobile mapping, 3D mesh generation, and a ray launching based network simulator. We identify the challenges and demonstrate the functionality of such a pipeline. We preview an empirical evaluation in a realistic real-world environment.}, address = {Belfast, UK}, author = {Wahl, T. and Borrmann, D. and Bleier, M. and {N{\"u}chter}, A. and Wiemann, T. and H{\"a}nel, T. and Aschenbruck, N.}, booktitle = {Proceedings of the 23rd IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM '22)}, keywords = {myown}, month = {06}, pages = {1–4}, title = {{WIP: Real-world 3D models derived from mobile mapping for ray launching based propagation loss modeling}}, year = 2022 }
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  An innovative pick-up and transport robot system for casualty evacuation. Edlinger, R.; Föls, C.; Nüchter, A. In Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’22), pp. 67–73. Seville, Spain, 2022.
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  This paper addresses the search and rescue scenario Casualty Evacuation (CasEvac) at the European Land Robot Trial (ELROB). A disaster response robot can be sent into areas to rescue victims where it is too dangerous for human rescue due to environmental issues like the danger of collapse or radioactivity. If injured persons are no longer able to move, the robot must be able to rescue them from the danger zone. This paper addresses this scenario and describes our system design, the manipulator tool and the innovative control mechanism for transporting victims. The experiment was tested at the competition and compared with other solutions from the participating teams and currently implemented developments.

  @inproceedings{SSRR2022_1, abstract = {This paper addresses the search and rescue scenario Casualty Evacuation (CasEvac) at the European Land Robot Trial (ELROB). A disaster response robot can be sent into areas to rescue victims where it is too dangerous for human rescue due to environmental issues like the danger of collapse or radioactivity. If injured persons are no longer able to move, the robot must be able to rescue them from the danger zone. This paper addresses this scenario and describes our system design, the manipulator tool and the innovative control mechanism for transporting victims. The experiment was tested at the competition and compared with other solutions from the participating teams and currently implemented developments.}, address = {Seville, Spain}, author = {Edlinger, R. and F{\"o}ls, C. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '22)}, keywords = {myown}, month = 11, pages = {67–73}, title = {{A}n innovative pick-up and transport robot system for casualty evacuation}, year = 2022 }
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  Trajectory Optimization and Following for a Three Degrees of Freedom Overactuated Floating Platform. Bredenbeck, A.; Vyas, S.; Zwick, M.; Borrmann, D.; Olivares-Mendez, M.A.; Nüchter, A. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’22), pp. 4084–4091. Kyoto, Japan, 2022.
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  Applications of space robotics, such as Active Space Debris Removal (ASDR), require representative test- ing before launch. A commonly used approach to emulate the microgravity environment in space are air-bearing based platforms on flat-floors, such as the European Space Agency’s Orbital Robotics and GNC Lab (ORGL). This work proposes a control architecture for a floating platform at the ORGL, equipped with eight solenoid-valve-based thrusters and one reaction wheel. The control architecture consists of two main components: a trajectory planner that finds optimal trajectories connecting two states and a trajectory follower that follows any physically feasible trajectory. The controller is first evaluated within an introduced simulation, achieving a 100\% success rate at finding and following trajectories to the origin within a Monte-Carlo test. Individual trajectories are also successfully followed by the physical system. In this work, we showcase the ability of the controller to reject disturbances and follow a straight-line trajectory within tens of centimeters.

  @inproceedings{IROS2022_2, abstract = {Applications of space robotics, such as Active Space Debris Removal (ASDR), require representative test- ing before launch. A commonly used approach to emulate the microgravity environment in space are air-bearing based platforms on flat-floors, such as the European Space Agency’s Orbital Robotics and GNC Lab (ORGL). This work proposes a control architecture for a floating platform at the ORGL, equipped with eight solenoid-valve-based thrusters and one reaction wheel. The control architecture consists of two main components: a trajectory planner that finds optimal trajectories connecting two states and a trajectory follower that follows any physically feasible trajectory. The controller is first evaluated within an introduced simulation, achieving a 100\% success rate at finding and following trajectories to the origin within a Monte-Carlo test. Individual trajectories are also successfully followed by the physical system. In this work, we showcase the ability of the controller to reject disturbances and follow a straight-line trajectory within tens of centimeters.}, address = {Kyoto, Japan}, author = {Bredenbeck, A. and Vyas, S. and Zwick, M. and Borrmann, D. and Olivares-Mendez, M.A. and N{\"u}chter, A.}, booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '22)}, keywords = {myown}, month = 10, pages = {4084–4091}, title = {{Trajectory Optimization and Following for a Three Degrees of Freedom Overactuated Floating Platform}}, year = 2022 }
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  Unconventional Trajectories for Mobile 3D Scanning and Mapping. Arzberger, F.; Zevering, J.; Bredenbeck, A.; Borrmann, D.; Nüchter, A. In Autonomous Mobile Mapping Robots, J. B\ce}}dkowski (ed.). IntechOpen, Rijeka, Croatia, 2022.
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  State-of-the-art LiDAR-based 3D scanning and mapping systems focus on scenarios where good sensing coverage is ensured, such as drones, wheeled robots, cars, or backpack-mounted systems. However, in some scenarios more unconventional sensor trajectories come naturally, e.g., rolling, descending, or oscillating back and forth, but the literature on these is relatively sparse. As a result, most implementations developed in the past are not able to solve the SLAM problem in such conditions. In this chapter, we propose a robust offline-batch SLAM system that is able to address more challenging trajectories, which are characterized by weak angles of incidence and limited FOV while scanning. The proposed SLAM system is an upgraded version of our previous work and takes as input the raw points and prior pose estimates, yet the latter are subject to large amounts of drift. Our approach is a two-staged algorithm where in the first stage coarse alignment is fast achieved by matching planar polygons. In the second stage, we utilize a graph-based SLAM algorithm for further refinement. We evaluate the mapping accu- racy of the algorithm on our own recorded datasets using high-resolution ground truth maps, which are available from a TLS.

  @incollection{INTECH22A, abstract = {State-of-the-art LiDAR-based 3D scanning and mapping systems focus on scenarios where good sensing coverage is ensured, such as drones, wheeled robots, cars, or backpack-mounted systems. However, in some scenarios more unconventional sensor trajectories come naturally, e.g., rolling, descending, or oscillating back and forth, but the literature on these is relatively sparse. As a result, most implementations developed in the past are not able to solve the SLAM problem in such conditions. In this chapter, we propose a robust offline-batch SLAM system that is able to address more challenging trajectories, which are characterized by weak angles of incidence and limited FOV while scanning. The proposed SLAM system is an upgraded version of our previous work and takes as input the raw points and prior pose estimates, yet the latter are subject to large amounts of drift. Our approach is a two-staged algorithm where in the first stage coarse alignment is fast achieved by matching planar polygons. In the second stage, we utilize a graph-based SLAM algorithm for further refinement. We evaluate the mapping accu- racy of the algorithm on our own recorded datasets using high-resolution ground truth maps, which are available from a TLS.}, address = {Rijeka, Croatia}, author = {Arzberger, F. and Zevering, J. and Bredenbeck, A. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {{A}utonomous {M}obile {M}apping {R}obots}, chapter = 9, editor = {B{\c{e}}dkowski, J.}, keywords = {myown}, publisher = {IntechOpen}, title = {{U}nconventional {T}rajectories for {M}obile {3D} {S}canning and {M}apping}, year = 2022 }
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  Visuelle Odometrie und SLAM für die Bewegungs-kompensation und mobile Kartierung mit einem optischen 3D-Unterwassersensor. Bleier, M.; Munkelt, C.; Heinze, M.; Bräuer-Burchardt, C.; Lauterbach, H. A.; van der Lucht, J.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2022, Jade Hochschule, pp. 394–405. Wichmann, 2022.
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  Im Projekt UWSensor wurde ein neuartiger optischer 3D-Unterwassersensor basierend auf Streifenlichtprojektion mit einem GOBO-Projektor entwickelt. Das Sensorsystem ermöglicht eine flächige 3D-Erfassung mit hoher Genauigkeit und Abtastrate, sowie eine gleichzeitige Erfassung von Farbdaten. Dies erlaubt den Einsatz zur mobilen Kartierung und 3D-Erfassung mit einem Unterwasserfahrzeug. Dieser Beitrag beschäftigt sich mit der Bewegungsschätzung sowie der Fusion der Einzelscans in ein global konsistentes 3D-Modell. Hierbei wird zunächst visuelle Odometrie in Kombination mit einem faseroptischen Gyroskop genutzt, um die Eigenbewegung des Sensors zu schätzen. Die daraus latenzarm abgeleiteten Posen werden dem Live-Aufnahmesystem des Sensors bereitgestellt, um eine online-Bewegungskompensation der den 3D Scans zugrundeliegenden Serie von Kamerabildern zu realisieren. Anschließend wird eine mehrstufigen Registrierungsstrategie angewendet, um die Schätzung der Trajektorie weiter zu verfeinern. Zunächst wird mittels des Iterative Closest Point (ICP) Algorithmus jede 3D-Punktwolke sequentiell gegen ihre Vorgänger registriert. Da sich kleine Restfehler in der Registrierung akkumulieren, erfolgt im nächsten Schritt eine zweite Registrierung mittels eines zeitkontinuierlichen ICP-Verfahren. Hierbei werden mehrere Punktwolken zu Teilkarten zusammengefasst und gegeneinander registriert, wobei die Verbesserungen der Trajektorie im Anschluss wiederum auf die einzelnen Posen der Punktwolken verteilt werden, um die Kontinuität der Trajektorie zu bewahren. In diesem Registrierungsschritt werden auch Schleifen in der Trajektorie erkannt und geschlossen, um den Drift zu korrigieren. Für die Kalibrierung des Sensorsystems wurde eine Kombination von Aufnahmen in Luft und im Wasser eingesetzt. Das Verfahren wurde auf dynamischen Aufnahmen mit dem neuentwickelten Sensorsystem in einem Wasserbecken getestet und evaluiert. Hierbei wurden sowohl bekannte Testkörper mit bewegtem Sensor im Wasser eingescannt, als auch die berechneten Trajektorien anhand der Bewegungsdaten des Portalsystems validiert.

  @inproceedings{3DTAGE2022_2, abstract = {Im Projekt UWSensor wurde ein neuartiger optischer 3D-Unterwassersensor basierend auf Streifenlichtprojektion mit einem GOBO-Projektor entwickelt. Das Sensorsystem ermöglicht eine flächige 3D-Erfassung mit hoher Genauigkeit und Abtastrate, sowie eine gleichzeitige Erfassung von Farbdaten. Dies erlaubt den Einsatz zur mobilen Kartierung und 3D-Erfassung mit einem Unterwasserfahrzeug. Dieser Beitrag beschäftigt sich mit der Bewegungsschätzung sowie der Fusion der Einzelscans in ein global konsistentes 3D-Modell. Hierbei wird zunächst visuelle Odometrie in Kombination mit einem faseroptischen Gyroskop genutzt, um die Eigenbewegung des Sensors zu schätzen. Die daraus latenzarm abgeleiteten Posen werden dem Live-Aufnahmesystem des Sensors bereitgestellt, um eine online-Bewegungskompensation der den 3D Scans zugrundeliegenden Serie von Kamerabildern zu realisieren. Anschließend wird eine mehrstufigen Registrierungsstrategie angewendet, um die Schätzung der Trajektorie weiter zu verfeinern. Zunächst wird mittels des Iterative Closest Point (ICP) Algorithmus jede 3D-Punktwolke sequentiell gegen ihre Vorgänger registriert. Da sich kleine Restfehler in der Registrierung akkumulieren, erfolgt im nächsten Schritt eine zweite Registrierung mittels eines zeitkontinuierlichen ICP-Verfahren. Hierbei werden mehrere Punktwolken zu Teilkarten zusammengefasst und gegeneinander registriert, wobei die Verbesserungen der Trajektorie im Anschluss wiederum auf die einzelnen Posen der Punktwolken verteilt werden, um die Kontinuität der Trajektorie zu bewahren. In diesem Registrierungsschritt werden auch Schleifen in der Trajektorie erkannt und geschlossen, um den Drift zu korrigieren. Für die Kalibrierung des Sensorsystems wurde eine Kombination von Aufnahmen in Luft und im Wasser eingesetzt. Das Verfahren wurde auf dynamischen Aufnahmen mit dem neuentwickelten Sensorsystem in einem Wasserbecken getestet und evaluiert. Hierbei wurden sowohl bekannte Testkörper mit bewegtem Sensor im Wasser eingescannt, als auch die berechneten Trajektorien anhand der Bewegungsdaten des Portalsystems validiert.}, author = {Bleier, M. and Munkelt, C. and Heinze, M. and Br{\"a}uer-Burchardt, C. and Lauterbach, H. A. and van der Lucht, J. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2022, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {394–405}, publisher = {Wichmann}, title = {{Visuelle Odometrie und SLAM für die Bewegungs-kompensation und mobile Kartierung mit einem optischen 3D-Unterwassersensor}}, year = 2022 }

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  L.U.N.A. - A Laser-Mapping Unidirectional Navigation Actuator. Zevering, J.; Bredenbeck, A.; Arzberger, F.; Borrmann, D.; Nüchter, A. In Proceedings of the 17th International Symposium of Experimental Robotics (ISER ’20), of Springer Proceedings in Advanced Robotics, pp. 85–94. Valetta, Malta, 2021.
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  This paper proposes an autonomous approach to 3D mapping using the concept of impulse by conservation of angular momentum (IBCOAM) as a unidirectional drive to roll a 2D laser scanner in an IMU equipped, pose-tracked spherical robot system. An experimental prototype of the robot is introduced, giving details about the hardware. The laser scanning results as well as the IBCOAM drive data that have been gathered using the prototype are analyzed, revealing technical challenges.

  @inproceedings{ISER2021, abstract = {This paper proposes an autonomous approach to 3D mapping using the concept of impulse by conservation of angular momentum (IBCOAM) as a unidirectional drive to roll a 2D laser scanner in an IMU equipped, pose-tracked spherical robot system. An experimental prototype of the robot is introduced, giving details about the hardware. The laser scanning results as well as the IBCOAM drive data that have been gathered using the prototype are analyzed, revealing technical challenges.}, address = {Valetta, Malta}, author = {Zevering, J. and Bredenbeck, A. and Arzberger, F. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the 17th International Symposium of Experimental Robotics (ISER '20)}, keywords = {myown}, month = {03}, pages = {85–94}, series = {Springer Proceedings in Advanced Robotics}, title = {{{L.U.N.A.} - A Laser-Mapping Unidirectional Navigation Actuator}}, year = 2021 }
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  RADLER -- A UNICYCLE AS A LOW-COST RADIAL LASER SCANNER. Borrmann, D.; Jörissen, S.; Nüchter, A. In Proceedings of the ISPRS Congress 2021, of ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 65–72. Nice, France, 2021.
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  In recent years a wide range of 3D multi sensor systems for various applications has been proposed. Each of them has its own benefits and limitations. This paper proposes a modified unicycle with a 2D laser profiler attached to the wheel axle, thus creating a radial 3D scanning pattern. This novel low-cost device combines the advantages of wheeled scanning equipment with those of wearable or hand-held devices. After presenting the hardware setup and the sensor integration, the results are evaluated using four test scenarios and a terrestrial laser scanner for comparison.

  @inproceedings{ISPRSCongress2021b, abstract = {In recent years a wide range of 3D multi sensor systems for various applications has been proposed. Each of them has its own benefits and limitations. This paper proposes a modified unicycle with a 2D laser profiler attached to the wheel axle, thus creating a radial 3D scanning pattern. This novel low-cost device combines the advantages of wheeled scanning equipment with those of wearable or hand-held devices. After presenting the hardware setup and the sensor integration, the results are evaluated using four test scenarios and a terrestrial laser scanner for comparison.}, address = {Nice, France}, author = {Borrmann, D. and J{\"o}rissen, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the ISPRS Congress 2021}, keywords = {myown}, number = {V-1-2021}, pages = {65–72}, series = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, title = {RADLER – A UNICYCLE AS A LOW-COST RADIAL LASER SCANNER}, year = 2021 }
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  Combining LiDAR Scan Matching with Stereo Visual Odometry Using Curvefusion. Du, S.; Li, X.; Lauterbach, H. A.; Borrmann, D.; Nüchter, A. In Proceedings of the IEEE International Conference on Computer, Control and Robotics (ICCCR ’21), pp. 335–339. 2021.
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  In this paper, we present a novel algorithm, namely Curvefusion for integrating LiDAR scan matching with stereo visual odometry. First, 6-DOF pose trajectories are estimated by utilizing SOFT odometry, which is the state of the art stereo visual odometry based on feature selection and tracking, and the well-known ICP scan matching algorithm, respectively. Second, a deformation-based multi-sensor fusion method, namely curvefusion is applied. The proposed fusion method does not rely on a sensor model. As long as the trajectories of the sensors to be fused are given, we can obtain an optimized fusion trajectory, which greatly improves the computational efficiency. Experiments based on publicly available KITTI data set show that the proposed method outperforms or achieves similar performance compared with the state-of-the-art odometry methods.

  @inproceedings{ICCCR2021, abstract = {In this paper, we present a novel algorithm, namely Curvefusion for integrating LiDAR scan matching with stereo visual odometry. First, 6-DOF pose trajectories are estimated by utilizing SOFT odometry, which is the state of the art stereo visual odometry based on feature selection and tracking, and the well-known ICP scan matching algorithm, respectively. Second, a deformation-based multi-sensor fusion method, namely curvefusion is applied. The proposed fusion method does not rely on a sensor model. As long as the trajectories of the sensors to be fused are given, we can obtain an optimized fusion trajectory, which greatly improves the computational efficiency. Experiments based on publicly available KITTI data set show that the proposed method outperforms or achieves similar performance compared with the state-of-the-art odometry methods.}, author = {{Du}, S. and {Li}, X. and {Lauterbach}, H. A. and {Borrmann}, D. and {N{\"u}chter}, A.}, booktitle = {Proceedings of the IEEE International Conference on Computer, Control and Robotics (ICCCR '21)}, keywords = {myown}, pages = {335–339}, title = {Combining LiDAR Scan Matching with Stereo Visual Odometry Using Curvefusion}, year = 2021 }
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  Testing AGV Mobility Control Method for MANET Coverage Optimization using Procedural Generation. Sauer, C.; Lyczkowski, E.; Schmidt, M.; Nüchter, A.; Hoßfeld, T. In Proceedings of the ACM Conference MSWiM: Modeling, Analysis and Simulation of Wireless and Mobile Systems. Alicante, Spain, 2021.
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  In industrial applications continuous wireless connectivity of mobile clients can rarely by guaranteed. Lack of communication negatively impacts the performance of industrial automation systems, e.g. Automated Guided Vehicle (AGV) fleets. Utilizing industrial Mobile Ad-hoc NETworks (MANETs) and adaptive positioning systems can reduce the number of disconnections in these AGV fleets. Therefore the performance of the mobile systems (e.g. AGV fleet) is improved and factory efficiency increased. In this work procedural simulation is used to examine wireless communication in industrial applications. This methods enables the observation of the interaction of mobility control system, network status and robotic system performance independently from a specific environment or scenario. Novel insights on the effectiveness of ad-hoc communication in industrial applications and the correlation of AGV fleet connectedness and AGV fleet transport performance are presented. Additionally a control method is proposed, which improves the network coverage of an industrial MANET and efficiency of AGV fleets.

  @inproceedings{MSWiM_2021, abstract = {In industrial applications continuous wireless connectivity of mobile clients can rarely by guaranteed. Lack of communication negatively impacts the performance of industrial automation systems, e.g. Automated Guided Vehicle (AGV) fleets. Utilizing industrial Mobile Ad-hoc NETworks (MANETs) and adaptive positioning systems can reduce the number of disconnections in these AGV fleets. Therefore the performance of the mobile systems (e.g. AGV fleet) is improved and factory efficiency increased. In this work procedural simulation is used to examine wireless communication in industrial applications. This methods enables the observation of the interaction of mobility control system, network status and robotic system performance independently from a specific environment or scenario. Novel insights on the effectiveness of ad-hoc communication in industrial applications and the correlation of AGV fleet connectedness and AGV fleet transport performance are presented. Additionally a control method is proposed, which improves the network coverage of an industrial MANET and efficiency of AGV fleets.}, address = {Alicante, Spain}, author = {Sauer, C. and Lyczkowski, E. and Schmidt, M. and N{\"u}chter, A. and Ho{\ss}feld, T.}, booktitle = {Proceedings of the ACM Conference MSWiM: Modeling, Analysis and Simulation of Wireless and Mobile Systems}, keywords = {author}, title = {{Testing AGV Mobility Control Method for MANET Coverage Optimization using Procedural Generation}}, year = 2021 }
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  Measuring internal quality traits in egg by 3D laser imaging. Mollazade, K.; Jörissen, S.; Nüchter, A. In Journal of Food Engineering, 291(02), pp. 1–14. 2021.
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  Quality of the egg is examined before the production process in the food industry. In this study, a 3D laser scanning approach was developed to measure internal quality traits of the egg. Experiments were carried out on 450 chicken egg samples in different freshness stages. Spectroscopic analysis showed 600–700 nm would be a suitable wavelength region for laser scanning. The quasi-liquid transparency nature of the albumin introduced issues to laser scanning, which were fixed by two solutions: 1. coating of the thick albumin region with Talcum powder before scanning, and 2. training a multilayer perceptron neural network to map the 2D shape features of the thick albumin region to the actual albumin height values. Results indicated that the yolk index and Haugh unit are reliably measured using 3D scanning of the yolk part (R = 0.97 and RMSE = 0.04) and the 2D shape analysis of the thick albumin region (R = 0.84 and RMSE = 6.53), respectively.

  @article{JFOODENG2021, abstract = {Quality of the egg is examined before the production process in the food industry. In this study, a 3D laser scanning approach was developed to measure internal quality traits of the egg. Experiments were carried out on 450 chicken egg samples in different freshness stages. Spectroscopic analysis showed 600–700 nm would be a suitable wavelength region for laser scanning. The quasi-liquid transparency nature of the albumin introduced issues to laser scanning, which were fixed by two solutions: 1. coating of the thick albumin region with Talcum powder before scanning, and 2. training a multilayer perceptron neural network to map the 2D shape features of the thick albumin region to the actual albumin height values. Results indicated that the yolk index and Haugh unit are reliably measured using 3D scanning of the yolk part (R = 0.97 and RMSE = 0.04) and the 2D shape analysis of the thick albumin region (R = 0.84 and RMSE = 6.53), respectively.}, author = {Mollazade, K. and J{\"o}rissen, S. and N{\"u}chter, A.}, journal = {Journal of Food Engineering}, keywords = {author}, month = {02}, number = {02}, pages = {1–14}, title = {Measuring internal quality traits in egg by 3D laser imaging}, volume = 291, year = 2021 }
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  DAEDALUS -- Descent And Exploration in Deep Autonomy of Lava Underground Structures. Rossi, A. P.; Maurelli, F.; Unnithan, V.; Dreger, H.; Mathewos, K.; Pradhan, N.; Corbeanu, D.-A.; Pozzobon, R.; Massironi, M.; Ferrari, S.; Pernechele, C.; Paoletti, L.; Simioni, E.; Pajola, M.; Santagata, T.; Borrmann, D.; Nüchter, A.; Bredenbeck, A.; Zevering, J.; Arzberger, F.; Mantilla, C. A. R. In of Uni Wuerzburg Research Notes in Robotics and Telematics, pp. 1–190. Julius Maximilian University of Würzburg, 2021.
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  The DAEDALUS mission concept aims at exploring and characterising the entrance and initial part of Lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities. The mission concept addresses specifically the identification and characterisation of potential resources for future ESA exploration, the local environment of the subsurface and its geologic and compositional structure. A sphere is ideally suited to protect sensors and scientific equipment in rough, uneven environments. It will house laser scanners, cameras and ancillary payloads. The sphere will be lowered into the skylight and will explore the entrance shaft, associated caverns and conduits. Lidar (light detection and ranging) systems produce 3D models with high spatial accuracy independent of lighting conditions and visible features. Hence this will be the primary exploration toolset within the sphere. The additional payload that can be accommodated in the robotic sphere consists of camera systems with panoramic lenses and scanners such as multi-wavelength or single-photon scanners. A moving mass will trigger movements. The tether for lowering the sphere will be used for data communication and powering the equipment during the descending phase. Furthermore, the connector tether-sphere will host a WIFI access point, such that data of the conduit can be transferred to the surface relay station. During the exploration phase, the robot will be disconnected from the cable, and will use wireless communication. Emergency autonomy software will ensure that in case of loss of communication, the robot will continue the nominal mission.

  @book{DAEDALUS2021, abstract = {The DAEDALUS mission concept aims at exploring and characterising the entrance and initial part of Lunar lava tubes within a compact, tightly integrated spherical robotic device, with a complementary payload set and autonomous capabilities. The mission concept addresses specifically the identification and characterisation of potential resources for future ESA exploration, the local environment of the subsurface and its geologic and compositional structure. A sphere is ideally suited to protect sensors and scientific equipment in rough, uneven environments. It will house laser scanners, cameras and ancillary payloads. The sphere will be lowered into the skylight and will explore the entrance shaft, associated caverns and conduits. Lidar (light detection and ranging) systems produce 3D models with high spatial accuracy independent of lighting conditions and visible features. Hence this will be the primary exploration toolset within the sphere. The additional payload that can be accommodated in the robotic sphere consists of camera systems with panoramic lenses and scanners such as multi-wavelength or single-photon scanners. A moving mass will trigger movements. The tether for lowering the sphere will be used for data communication and powering the equipment during the descending phase. Furthermore, the connector tether-sphere will host a WIFI access point, such that data of the conduit can be transferred to the surface relay station. During the exploration phase, the robot will be disconnected from the cable, and will use wireless communication. Emergency autonomy software will ensure that in case of loss of communication, the robot will continue the nominal mission.}, address = {Julius Maximilian University of W{\"u}rzburg}, author = {Rossi, A. P. and Maurelli, F. and Unnithan, V. and Dreger, H. and Mathewos, K. and Pradhan, N. and Corbeanu, D.-A. and Pozzobon, R. and Massironi, M. and Ferrari, S. and Pernechele, C. and Paoletti, L. and Simioni, E. and Pajola, M. and Santagata, T. and Borrmann, D. and N{\"u}chter, A. and Bredenbeck, A. and Zevering, J. and Arzberger, F. and Mantilla, C. A. R.}, keywords = {myown}, month = {03}, pages = {1–190}, series = {Uni Wuerzburg Research Notes in Robotics and Telematics}, title = {DAEDALUS – Descent And Exploration in Deep Autonomy of Lava Underground Structures}, year = 2021 }
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  Marius Hills Skylight hazard characterization as a possible landing site for lunar subsurface exploration. Pozzobon, R.; Rossi, A. P.; Ferrari, S.; Massironi, M.; Pajola, M.; Nüchter, A.; Borrmann, D.; Zevering, J.; Bredenbeck, A.; Arzberger, F.; Mantilla, C. A. Reyes; Maurelli, F.; Unnithan, V.; Dreger, H.; Mathewos, K.; Pradhan, N.; Pernechele, C.; Paoletti, L.; Simioni, E.; Santagata, T. In Proceedings of the 52nd Lunar and Planetary Science Conference (LPSC ’21). Universities Space Research Association, Lunar and Planetary Institute, virtual meeting, 2021.
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  @inproceedings{LPSC2012_1, address = {virtual meeting}, author = {Pozzobon, R. and Rossi, A. P. and Ferrari, S. and Massironi, M. and Pajola, M. and N{\"u}chter, A. and Borrmann, D. and Zevering, J. and Bredenbeck, A. and Arzberger, F. and Mantilla, C. A. Reyes and Maurelli, F. and Unnithan, V. and Dreger, H. and Mathewos, K. and Pradhan, N. and Pernechele, C. and Paoletti, L. and Simioni, E. and Santagata, T.}, booktitle = {Proceedings of the 52nd Lunar and Planetary Science Conference (LPSC '21)}, keywords = {myown}, month = {03}, organization = {Universities Space Research Association, Lunar and Planetary Institute}, title = {Marius Hills Skylight hazard characterization as a possible landing site for lunar subsurface exploration}, year = 2021 }
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  Lunar Caves Exploration with the DAEDALUS Spherical Robot. Borrmann, D.; Nüchter, A.; Bredenbeck, A.; Zevering, J.; Arzberger, F.; Mantilla, C. A. Reyes; Rossi, A. P.; Maurelli, F.; Unnithan, V.; Dreger, H.; Mathewos, K.; Pradhan, N.; Pozzobon, R.; Massironi, M.; Ferrari, S.; Pernechele, C.; Paoletti, L.; Simioni, E.; Pajola, M.; Santagata, T. In Proceedings of the 52nd Lunar and Planetary Science Conference (LPSC ’21). Universities Space Research Association, Lunar and Planetary Institute, virtual meeting, 2021.
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  @inproceedings{LPSC2012_2, address = {virtual meeting}, author = {Borrmann, D. and N{\"u}chter, A. and Bredenbeck, A. and Zevering, J. and Arzberger, F. and Mantilla, C. A. Reyes and Rossi, A. P. and Maurelli, F. and Unnithan, V. and Dreger, H. and Mathewos, K. and Pradhan, N. and Pozzobon, R. and Massironi, M. and Ferrari, S. and Pernechele, C. and Paoletti, L. and Simioni, E. and Pajola, M. and Santagata, T.}, booktitle = {Proceedings of the 52nd Lunar and Planetary Science Conference (LPSC '21)}, keywords = {myown}, month = {03}, organization = {Universities Space Research Association, Lunar and Planetary Institute}, title = {Lunar Caves Exploration with the DAEDALUS Spherical Robot}, year = 2021 }
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  Towards spherical robots for mobile mapping in human made environments. Arzberger, F.; Bredenbeck, A.; Zevering, J.; Borrmann, D.; Nüchter, A. In ISPRS Open Journal of Photogrammetry and Remote Sensing (OJPRS), 1, p. 100004. 2021.
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  Spherical robots are a format that has not been thoroughly explored for the application of mobile mapping. In contrast to other designs, it provides some unique advantages. Among those is a spherical shell that protects internal sensors and actuators from possible harsh environments, as well as an inherent rotation for locomotion that enables measurements in all directions. Mobile mapping always requires a high-precise pose knowledge to obtain consistent and correct environment maps. This is typically done by a combination of external reference sensors such as Global Navigation Satellite System (GNSS) measurements and inertial measurements or by coarsely estimating the pose using inertial measurement units (IMUs) and post processing the data by registering the different measurements to each other. In indoor environments, the GNSS reference is not an option. Hence many mobile mapping applications turn to the second option. An advantage of indoor environments is that human-made environments usually have a certain structure, such as parallel and perpendicular planes. We propose a registration procedure that exploits this structure by minimizing the distance of measured points to a corresponding plane. Further, we evaluate the procedure on a simulated dataset of an ideal corridor and on an experimentally acquired dataset with different motion profiles. We show that we nearly reproduce the ground truth for the simulated dataset and improve the average point-to-point distance to a reference scan in the experimental dataset. The presented algorithms are required to work completely autonomously.

  @article{JPRS_2018, abstract = {Spherical robots are a format that has not been thoroughly explored for the application of mobile mapping. In contrast to other designs, it provides some unique advantages. Among those is a spherical shell that protects internal sensors and actuators from possible harsh environments, as well as an inherent rotation for locomotion that enables measurements in all directions. Mobile mapping always requires a high-precise pose knowledge to obtain consistent and correct environment maps. This is typically done by a combination of external reference sensors such as Global Navigation Satellite System (GNSS) measurements and inertial measurements or by coarsely estimating the pose using inertial measurement units (IMUs) and post processing the data by registering the different measurements to each other. In indoor environments, the GNSS reference is not an option. Hence many mobile mapping applications turn to the second option. An advantage of indoor environments is that human-made environments usually have a certain structure, such as parallel and perpendicular planes. We propose a registration procedure that exploits this structure by minimizing the distance of measured points to a corresponding plane. Further, we evaluate the procedure on a simulated dataset of an ideal corridor and on an experimentally acquired dataset with different motion profiles. We show that we nearly reproduce the ground truth for the simulated dataset and improve the average point-to-point distance to a reference scan in the experimental dataset. The presented algorithms are required to work completely autonomously.}, author = {Arzberger, F. and Bredenbeck, A. and Zevering, J. and Borrmann, D. and N{\"u}chter, A.}, journal = {ISPRS Open Journal of Photogrammetry and Remote Sensing (OJPRS)}, keywords = {myown}, pages = 100004, title = {Towards spherical robots for mobile mapping in human made environments}, volume = 1, year = 2021 }
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  CALIBRATION AND VALIDATION OF THE INTEL T265 FOR VISUAL LOCALISATION AND TRACKING UNDERWATER. Appelt, T.; van der Lucht, J.; Bleier, M.; Nüchter, A. In Proceedings of the ISPRS Congress 2021, of The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 635–641. Nice, France, 2021.
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  Localization and navigation for autonomous underwater vehicle (AUV) has always been a major challenge and many situations complex solutions had to be devised. One of the main approaches is visual odometry using a stereo camera. In this study, the Intel T265 fisheye stereo camera has been calibrated and tested to determine it’s usability for localisation and navigation under water as an alternative to more complex systems. Firstly the Intel T265 fisheye stereo camera was appropriately calibrated inside a water filled container. This calibration consisting of camera and distortion parameters got programmed onto the T265 fisheye stereo camera to take the differences between land and underwater usage into account. Successive the calibration, the accuracy and the precision of the T265 fisheye stereo camera were tested using a linear, a circular and finally a chaotic motion. This includes a review of the localisation and tracking of the cameras visual odometry compared to a ground truth provided by an OptiTrack V120:Trio to account for scaling, accuracy and precision. Also experiments to determine the usability with fast chaotic motions were performed and analysed. Finally, a conclusion concerning the applicability of the Intel T265 fisheye stereo camera, the challenges using this model, the possibilities for low cost operations and the main challenges for future work is conducted.

  @inproceedings{ISPRSCongress2021a, abstract = {Localization and navigation for autonomous underwater vehicle (AUV) has always been a major challenge and many situations complex solutions had to be devised. One of the main approaches is visual odometry using a stereo camera. In this study, the Intel T265 fisheye stereo camera has been calibrated and tested to determine it’s usability for localisation and navigation under water as an alternative to more complex systems. Firstly the Intel T265 fisheye stereo camera was appropriately calibrated inside a water filled container. This calibration consisting of camera and distortion parameters got programmed onto the T265 fisheye stereo camera to take the differences between land and underwater usage into account. Successive the calibration, the accuracy and the precision of the T265 fisheye stereo camera were tested using a linear, a circular and finally a chaotic motion. This includes a review of the localisation and tracking of the cameras visual odometry compared to a ground truth provided by an OptiTrack V120:Trio to account for scaling, accuracy and precision. Also experiments to determine the usability with fast chaotic motions were performed and analysed. Finally, a conclusion concerning the applicability of the Intel T265 fisheye stereo camera, the challenges using this model, the possibilities for low cost operations and the main challenges for future work is conducted.}, address = {Nice, France}, author = {Appelt, T. and van der Lucht, J. and Bleier, M. and N{\"u}chter, A.}, booktitle = {Proceedings of the ISPRS Congress 2021}, keywords = {myown}, number = {XLIII-B2-2021}, pages = {635–641}, series = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, title = {CALIBRATION AND VALIDATION OF THE INTEL T265 FOR VISUAL LOCALISATION AND TRACKING UNDERWATER}, year = 2021 }
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  Indoor 3D: Overview on Scanning and Reconstruction Methods. Lehtola, V. V.; Nikoohemat, S.; Nüchter, A. In Handbook of Big Geospatial Data, M. Werner, Y.-Y. Chiang (eds.), pp. 55–97. Springer International Publishing, Cham, 2021.
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  This chapter covers the essentials regarding indoor 3D data, from scanning to reconstruction. It is aimed for education and professionals. The order of presentation is background, history in measurement method development, sensors, sensor systems, positioning algorithms, reconstruction, and applications. The authors' backgrounds are in indoor 3D, mobile laser scanning, indoor reconstruction, and robotics. In order to maintain a coherence in the text and provide some useful tools for the reader, we have selected to focus solely on the ICP version of simultaneous localization and mapping (SLAM). Regardless, this should give a solid base for the reader to understand other (e.g. probabilistic) indoor SLAM methods as well. Reconstruction algorithms (starting from room segmentation and opening detection) are discussed with the help of abundant figures. At the very end, we discuss future trends with a connection to the current applications and propose some exercise questions for students.

  @inbook{Lehtola2021, abstract = {This chapter covers the essentials regarding indoor 3D data, from scanning to reconstruction. It is aimed for education and professionals. The order of presentation is background, history in measurement method development, sensors, sensor systems, positioning algorithms, reconstruction, and applications. The authors' backgrounds are in indoor 3D, mobile laser scanning, indoor reconstruction, and robotics. In order to maintain a coherence in the text and provide some useful tools for the reader, we have selected to focus solely on the ICP version of simultaneous localization and mapping (SLAM). Regardless, this should give a solid base for the reader to understand other (e.g. probabilistic) indoor SLAM methods as well. Reconstruction algorithms (starting from room segmentation and opening detection) are discussed with the help of abundant figures. At the very end, we discuss future trends with a connection to the current applications and propose some exercise questions for students.}, address = {Cham}, author = {Lehtola, V. V. and Nikoohemat, S. and N{\"u}chter, A.}, booktitle = {Handbook of Big Geospatial Data}, editor = {Werner, Martin and Chiang, Yao-Yi}, keywords = {myown}, pages = {55–97}, publisher = {Springer International Publishing}, title = {Indoor 3D: Overview on Scanning and Reconstruction Methods}, year = 2021 }
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  Stability metrics and improved odometry prediction for tracked vehicles with tactile sensors. Edlinger, R.; Föls, C.; Froschauer, R.; Nüchter, A. In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’21), pp. 1–6. New York, USA, 2021.
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  @inproceedings{SSRR2021, address = {New York, USA}, author = {Edlinger, R. and F{\"o}ls, C. and Froschauer, R. and {N{\"u}chter}, A.}, booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '21)}, keywords = {myown}, month = 10, pages = {1–6}, title = {{Stability metrics and improved odometry prediction for tracked vehicles with tactile sensors}}, year = 2021 }
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  IMU-based pose-estimation for spherical robots with limited resources. Zevering, J.; Bredenbeck, A.; Arzberger, F.; Borrmann, D.; Nüchter, A. In Proceedings of the IEEE International Conference on Multisensor Fusion and Integration (MFI ’21). Karlsruhe, Germany, 2021.
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  @inproceedings{MFI2021, address = {Karlsruhe, Germany}, author = {Zevering, J. and Bredenbeck, A. and Arzberger, F. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference on Multisensor Fusion and Integration (MFI '21)}, keywords = {myown}, month = {09}, title = {IMU-based pose-estimation for spherical robots with limited resources}, year = 2021 }
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  Self-Supervised Point Set Local Descriptors for Point Cloud Registration. Yuan, Y.; Borrmann, D.; Hou, J.; Ma, Y.; Schwertfeger, S.; Nüchter, A. In Sensors, 21(2), p. 486. 2021.
  • [ Abstract ]
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  Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous localization and mapping (SLAM) to further improve the trajectory. While state-of-the-art multi-sensor fusion methods mainly focus on probabilistic methods, our approach instead adopts a deformation-based method to optimize poses. To this end, a similarity metric for curved shapes is introduced into the robotics community to fuse the estimated trajectories. Additionally, a shape-based point correspondence estimation method is applied to the multi-sensor time calibration. Experiments show that the proposed fusion method can achieve relatively better accuracy, even if the error of the trajectory before fusion is large, which demonstrates that our method can still maintain a certain degree of accuracy in an environment where typical pose estimation methods have poor performance. In addition, the proposed time-calibration method also achieves high accuracy in estimating point correspondences.

  @article{MDPI2021, abstract = {Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous localization and mapping (SLAM) to further improve the trajectory. While state-of-the-art multi-sensor fusion methods mainly focus on probabilistic methods, our approach instead adopts a deformation-based method to optimize poses. To this end, a similarity metric for curved shapes is introduced into the robotics community to fuse the estimated trajectories. Additionally, a shape-based point correspondence estimation method is applied to the multi-sensor time calibration. Experiments show that the proposed fusion method can achieve relatively better accuracy, even if the error of the trajectory before fusion is large, which demonstrates that our method can still maintain a certain degree of accuracy in an environment where typical pose estimation methods have poor performance. In addition, the proposed time-calibration method also achieves high accuracy in estimating point correspondences.}, author = {Yuan, Y. and Borrmann, D. and Hou, J. and Ma, Y. and Schwertfeger, S. and N{\"u}chter, A.}, journal = {Sensors}, keywords = {sys:relevantfor:uniwue_cs7}, month = {01}, number = 2, pages = 486, title = {Self-Supervised Point Set Local Descriptors for Point Cloud Registration}, volume = 21, year = 2021 }
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  SCOUT3D -- ein Unterwasser-Laserscanner für mobile Kartierung. Bleier, M.; van der Lucht, J.; Nüchter, A. In Allgemeine Vermessungs-Nachrichten (AVN), 128(4), pp. 171–180. 2021.
  • [ Abstract ]
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  Dieser Beitrag stellt einen neu entwickelten Unterwasser-Laserscanner kombiniert mit einem auf GNSS basierenden System zur Bestimmung der Trajektorie vor. Dies ermöglicht es, von einem Boot aus den Grund oder Objekte in flachen Gewässern zu kartieren. Das System verfügt über eine Über- und eine Unterwasserkomponente. Über Wasser werden zwei kostengünstige Multiband-GNSS-Empfänger mit einer Antennenbasislinie von einem Meter für die RTK-Positionierung mit Kurswinkel verwendet. Die kompletten sechs Freiheitsgrade der Positionierung werden durch die Fusionierung der Satellitennavigationsdaten und einer MEMS-basierten INS bestimmt. Die 3D-Daten im Wasser werden mit einem Structured-Light-Scanner erfasst, der aus einer lichtempfindlichen Unterwasserkamera und einem grünen Kreuzlinienlaserprojektor besteht. Es werden die Entwicklung des Systems und die verwendeten Hardwarekomponenten beschrieben und erste Ergebnisse präsentiert. Hierzu wurden Testobjekte in einem Wassertank sowohl von einem Stativ aus als auch von einer bewegten, schwimmenden Plattform aus gescannt. Eine Auswertung der entstanden Punktwolken findet durch einen Vergleich mit in der Szene platzierten Prüfkörpern und in Luft erzeugten Referenzscans der Testobjekte statt. Die Experimente evaluieren Auflösungsvermögen sowie Genauigkeit der Scans.

  @article{AVN2021, abstract = {Dieser Beitrag stellt einen neu entwickelten Unterwasser-Laserscanner kombiniert mit einem auf GNSS basierenden System zur Bestimmung der Trajektorie vor. Dies ermöglicht es, von einem Boot aus den Grund oder Objekte in flachen Gewässern zu kartieren. Das System verfügt über eine Über- und eine Unterwasserkomponente. Über Wasser werden zwei kostengünstige Multiband-GNSS-Empfänger mit einer Antennenbasislinie von einem Meter für die RTK-Positionierung mit Kurswinkel verwendet. Die kompletten sechs Freiheitsgrade der Positionierung werden durch die Fusionierung der Satellitennavigationsdaten und einer MEMS-basierten INS bestimmt. Die 3D-Daten im Wasser werden mit einem Structured-Light-Scanner erfasst, der aus einer lichtempfindlichen Unterwasserkamera und einem grünen Kreuzlinienlaserprojektor besteht. Es werden die Entwicklung des Systems und die verwendeten Hardwarekomponenten beschrieben und erste Ergebnisse präsentiert. Hierzu wurden Testobjekte in einem Wassertank sowohl von einem Stativ aus als auch von einer bewegten, schwimmenden Plattform aus gescannt. Eine Auswertung der entstanden Punktwolken findet durch einen Vergleich mit in der Szene platzierten Prüfkörpern und in Luft erzeugten Referenzscans der Testobjekte statt. Die Experimente evaluieren Auflösungsvermögen sowie Genauigkeit der Scans.}, author = {Bleier, M. and van der Lucht, J. and N{\"u}chter, A.}, journal = {Allgemeine Vermessungs-Nachrichten (AVN)}, keywords = {sys:relevantfor:uniwue_cs7}, month = {08}, number = 4, pages = {171–180}, title = {SCOUT3D – ein Unterwasser-Laserscanner für mobile Kartierung}, volume = 128, year = 2021 }

• 
  Laserscanbasierte Ändreungsanalyse am Beispiel der Langen Anna auf Helgoland. Borrmann, D.; Lauterbach, H.; Houshiar, H.; Rossi, A. Pio; Unnitham, V.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2020, Jade Hochschule, pp. 186–197. 2020.
  • [ Abstract ]
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  Die "`Lange Anna"' ist das Wahrzeichen der Deutschen Hochseeinsel Helgoland. Durch seinen Standort an der Nordspitze der Insel ist der Buntsandsteinfelsen durch von Wind und Wasser verursachte Erosionen gefährdet. In einem Zeitraum von fünf Jahren wurden wiederholt an mehreren Standorten um die "`Lange Anna"' mit einem Riegl VZ-400 Laserscans aufgenommen. Dieser Beitrag evaluiert Methoden, um die Veränderungen automatisch zu dokumentieren und zu analysieren. Dies beinhaltet zwei grundlegende Arbeitsschritte, die in 3DTK (The 3D Toolkit) umgesetzt sind. Zuerst werden die Daten von mehreren Standpunkten in einem gemeinsamen Koordinatensystem registriert. Anschließend wird die Änderung am Gestein quantitativ erfasst und beschrieben. Dieser zweite Arbeitsschritt stellt den Schwerpunkt des Beitrags dar. Zwei Distanzmaße werden für diesen Zweck evaluiert, Punkt-zu-Punkt und Punkt-zu-Ebene-Distanzen.

  @inproceedings{3DTAGE2020_1, abstract = {Die "`Lange Anna"' ist das Wahrzeichen der Deutschen Hochseeinsel Helgoland. Durch seinen Standort an der Nordspitze der Insel ist der Buntsandsteinfelsen durch von Wind und Wasser verursachte Erosionen gefährdet. In einem Zeitraum von fünf Jahren wurden wiederholt an mehreren Standorten um die "`Lange Anna"' mit einem Riegl VZ-400 Laserscans aufgenommen. Dieser Beitrag evaluiert Methoden, um die Veränderungen automatisch zu dokumentieren und zu analysieren. Dies beinhaltet zwei grundlegende Arbeitsschritte, die in 3DTK (The 3D Toolkit) umgesetzt sind. Zuerst werden die Daten von mehreren Standpunkten in einem gemeinsamen Koordinatensystem registriert. Anschließend wird die Änderung am Gestein quantitativ erfasst und beschrieben. Dieser zweite Arbeitsschritt stellt den Schwerpunkt des Beitrags dar. Zwei Distanzmaße werden für diesen Zweck evaluiert, Punkt-zu-Punkt und Punkt-zu-Ebene-Distanzen.}, author = {Borrmann, D. and Lauterbach, H. and Houshiar, H. and Rossi, A. Pio and Unnitham, V. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2020, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {186–197}, title = {{Laserscanbasierte {\"A}ndreungsanalyse am Beispiel der Langen Anna auf Helgoland}}, year = 2020 }
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  Analytical Change Detection on the KITTI Dataset. Schauer, J.; Nüchter, A. In Proceedings of the 14th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV ’20). Shenzhen, China, 2020.
  • [ Abstract ]
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  We present an algorithm for explicit change detec- tion on 3D point cloud data from a mobile mapping scenario, namely the KITTI dataset. Our method is able to partition a 3D point cloud into static and dynamic points using ray traversal of a 3D voxel grid. We are thus not using a machine learning approach or RGB camera data but instead compute the intersections of the scene volume with the lines-of-sight between the sensor and the measured points. Our approach does thus not require any object detection or tracking and has comparatively low requirements on the hardware. While our earlier work focused on dense point clouds from terrestrial 3D laser scans, here we investigate its application on the sparse 3D point clouds produced by a Velodyne laser range finder in a mobile mapping scenario and compare our results to two competing implementations using the ground truth annotation from FuseMODNet for a quantitative analysis. We also introduce spherical quadtree point cloud reduction as a way to only work on less than 1\% of the original data, making processing multiple times faster while at the same time producing results with equivalent $F_1$ scores.

  @inproceedings{ICARCV2020, abstract = {We present an algorithm for explicit change detec- tion on 3D point cloud data from a mobile mapping scenario, namely the KITTI dataset. Our method is able to partition a 3D point cloud into static and dynamic points using ray traversal of a 3D voxel grid. We are thus not using a machine learning approach or RGB camera data but instead compute the intersections of the scene volume with the lines-of-sight between the sensor and the measured points. Our approach does thus not require any object detection or tracking and has comparatively low requirements on the hardware. While our earlier work focused on dense point clouds from terrestrial 3D laser scans, here we investigate its application on the sparse 3D point clouds produced by a Velodyne laser range finder in a mobile mapping scenario and compare our results to two competing implementations using the ground truth annotation from FuseMODNet for a quantitative analysis. We also introduce spherical quadtree point cloud reduction as a way to only work on less than 1\% of the original data, making processing multiple times faster while at the same time producing results with equivalent $F_1$ scores.}, address = {Shenzhen, China}, author = {Schauer, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the 14th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV '20)}, keywords = {myown}, month = 12, title = {{Analytical Change Detection on the KITTI Dataset}}, year = 2020 }
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  SCOUT3D -- ein Unterwasser-Laserscanner für mobile Kartierung. Bleier, M.; van der Lucht, J.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2020, Jade Hochschule, pp. 82–93. 2020.
  • [ Abstract ]
  • [ BibTeX ]
  • [ URL ]
  • [ Download ]
  Diese Arbeit stellt einen neu entwickelten Unterwasserlaserscanner kombiniert mit einem auf GNSS basierenden System zur Bestimmung der Trajektorie vor. Dies ermöglicht es, von einem Boot aus, den Grund oder Objekte in flachen Gewässern zu kartieren. Das System verfügt über eine Über- und eine Unterwasserkomponente. Über Wasser werden zwei kostengünstige Multiband-GNSS-Empfänger mit einer Antennenbasislinie von einem Meter für die RTK-Positionierung mit Kurswinkel verwendet. Die kompletten sechs Freiheitsgrade der Positionierung werden durch die Fusionierung der Satellitennavigationsdaten und einer MEMS-basierten INS bestimmt. Die 3D-Daten werden in Wasser mit einem Structured-Light-Scanner erfasst, der aus einer lichtempfindlichen Unterwasserkamera und einem grünen Kreuzlinienlaserprojektor besteht. Es wird die Entwicklung des Systems und die verwendeten Hardwarekomponenten beschrieben und erste Ergebnisse präsentiert. Hierzu wurde ein großes Testobjekt ein einem Wassertank sowohl von einem Stativ aus, als auch von einer bewegten, schwimmenden Plattform aus gescannt. Eine Auswertung der entstanden Punktwolken findet durch einen Vergleich mit in der Szene platzierten Prüfkörpern und in Luft erzeugten Referenzscans der Testobjekte statt.

  @inproceedings{3DTAGE2020_2, abstract = {Diese Arbeit stellt einen neu entwickelten Unterwasserlaserscanner kombiniert mit einem auf GNSS basierenden System zur Bestimmung der Trajektorie vor. Dies ermöglicht es, von einem Boot aus, den Grund oder Objekte in flachen Gewässern zu kartieren. Das System verfügt über eine Über- und eine Unterwasserkomponente. Über Wasser werden zwei kostengünstige Multiband-GNSS-Empfänger mit einer Antennenbasislinie von einem Meter für die RTK-Positionierung mit Kurswinkel verwendet. Die kompletten sechs Freiheitsgrade der Positionierung werden durch die Fusionierung der Satellitennavigationsdaten und einer MEMS-basierten INS bestimmt. Die 3D-Daten werden in Wasser mit einem Structured-Light-Scanner erfasst, der aus einer lichtempfindlichen Unterwasserkamera und einem grünen Kreuzlinienlaserprojektor besteht. Es wird die Entwicklung des Systems und die verwendeten Hardwarekomponenten beschrieben und erste Ergebnisse präsentiert. Hierzu wurde ein großes Testobjekt ein einem Wassertank sowohl von einem Stativ aus, als auch von einer bewegten, schwimmenden Plattform aus gescannt. Eine Auswertung der entstanden Punktwolken findet durch einen Vergleich mit in der Szene platzierten Prüfkörpern und in Luft erzeugten Referenzscans der Testobjekte statt.}, author = {Bleier, M. and van der Lucht, J. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2020, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {82–93}, title = {{SCOUT3D – ein Unterwasser-Laserscanner für mobile Kartierung}}, year = 2020 }
• 
  Feature Detection With a Constant FAR in Sparse 3-D Point Cloud Data. Lühr, D.; Adams, M.; Houshiar, H.; Borrmann, D.; Nüchter, A. In IEEE Transactions on Geoscience and Remote Sensing, 58(3), pp. 1877–1891. 2020.
  • [ Abstract ]
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  The detection of markers or reflectors within point cloud data (PCD) is often used for 3-D scan registration, mapping, and 3-D environmental modeling. However, the reliable detection of such artifacts is diminished when PCD is sparse and corrupted by detection and spatial errors, for example, when the sensing environment is contaminated by high dust levels, such as in mines. In the radar literature, constant false alarm rate (CFAR) processors provide solutions for extracting features within noisy data; however, their direct application to sparse, 3-D PCD is limited due to the difficulty in defining a suitable noise window. Therefore, in this article, CFAR detectors are derived, which are capable of processing a 2-D projected version of the 3-D PCD or which can directly process the 3-D PCD itself. Comparisons of their robustness, with respect to data sparsity, are made with various state-of-the-art feature detection methods, such as the Canny edge detector and random sampling consensus (RANSAC) shape detection methods.

  @article{tgrs2020, abstract = {The detection of markers or reflectors within point cloud data (PCD) is often used for 3-D scan registration, mapping, and 3-D environmental modeling. However, the reliable detection of such artifacts is diminished when PCD is sparse and corrupted by detection and spatial errors, for example, when the sensing environment is contaminated by high dust levels, such as in mines. In the radar literature, constant false alarm rate (CFAR) processors provide solutions for extracting features within noisy data; however, their direct application to sparse, 3-D PCD is limited due to the difficulty in defining a suitable noise window. Therefore, in this article, CFAR detectors are derived, which are capable of processing a 2-D projected version of the 3-D PCD or which can directly process the 3-D PCD itself. Comparisons of their robustness, with respect to data sparsity, are made with various state-of-the-art feature detection methods, such as the Canny edge detector and random sampling consensus (RANSAC) shape detection methods.}, author = {{L{\"u}hr}, D. and {Adams}, M. and {Houshiar}, H. and {Borrmann}, D. and {N{\"u}chter}, A.}, journal = {IEEE Transactions on Geoscience and Remote Sensing}, keywords = {author}, month = {03}, number = 3, pages = {1877–1891}, title = {{Feature Detection With a Constant FAR in Sparse 3-D Point Cloud Data}}, volume = 58, year = 2020 }
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  Curvefusion --- A Method for Combining Estimated Trajectories with Applications to SLAM and Time-Calibration. Du, S.; Lauterbach, H. A.; Li, X.; Demisse, G. G.; Borrmann, D.; Nüchter, A. In Sensors, 20(23), p. 6918. 2020.
  • [ Abstract ]
  • [ BibTeX ]
  • [ URL ]
  • [ DOI ]
  • [ Download ]
  Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous localization and mapping (SLAM) to further improve the trajectory. While state-of-the-art multi-sensor fusion methods mainly focus on probabilistic methods, our approach instead adopts a deformation-based method to optimize poses. To this end, a similarity metric for curved shapes is introduced into the robotics community to fuse the estimated trajectories. Additionally, a shape-based point correspondence estimation method is applied to the multi-sensor time calibration. Experiments show that the proposed fusion method can achieve relatively better accuracy, even if the error of the trajectory before fusion is large, which demonstrates that our method can still maintain a certain degree of accuracy in an environment where typical pose estimation methods have poor performance. In addition, the proposed time-calibration method also achieves high accuracy in estimating point correspondences.

  @article{MDPI2020, abstract = {Mapping and localization of mobile robots in an unknown environment are essential for most high-level operations like autonomous navigation or exploration. This paper presents a novel approach for combining estimated trajectories, namely curvefusion. The robot used in the experiments is equipped with a horizontally mounted 2D profiler, a constantly spinning 3D laser scanner and a GPS module. The proposed algorithm first combines trajectories from different sensors to optimize poses of the planar three degrees of freedom (DoF) trajectory, which is then fed into continuous-time simultaneous localization and mapping (SLAM) to further improve the trajectory. While state-of-the-art multi-sensor fusion methods mainly focus on probabilistic methods, our approach instead adopts a deformation-based method to optimize poses. To this end, a similarity metric for curved shapes is introduced into the robotics community to fuse the estimated trajectories. Additionally, a shape-based point correspondence estimation method is applied to the multi-sensor time calibration. Experiments show that the proposed fusion method can achieve relatively better accuracy, even if the error of the trajectory before fusion is large, which demonstrates that our method can still maintain a certain degree of accuracy in an environment where typical pose estimation methods have poor performance. In addition, the proposed time-calibration method also achieves high accuracy in estimating point correspondences.}, author = {Du, S. and Lauterbach, H. A. and Li, X. and Demisse, G. G. and Borrmann, D. and N{\"u}chter, A.}, journal = {Sensors}, keywords = {sys:relevantfor:uniwue_cs7}, month = 12, number = 23, pages = 6918, title = {Curvefusion — A Method for Combining Estimated Trajectories with Applications to SLAM and Time-Calibration}, volume = 20, year = 2020 }
• 
  Signed Distance Based Reconstruction for Exploration and Change Detection in Underground Mining Disaster Prevention. Koch, P.; Engelhardt, H.; May, S.; Schmidpeter, M.; Ziegler, J.; Nüchter, A. In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’20), pp. 1–6. 2020.
  • [ Abstract ]
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  This publication describes an application of a Truncated Signed Distance Mapping approach for disaster intervention in underground mine shafts through geometrical change detection of the shaft walls. The paper describes two main problems of such an approach (aligning two potentially huge point clouds and automatic change detection by comparing the reconstructed volumes) and explains in detail the proposed solution.

  @inproceedings{SSRR2020, abstract = {This publication describes an application of a Truncated Signed Distance Mapping approach for disaster intervention in underground mine shafts through geometrical change detection of the shaft walls. The paper describes two main problems of such an approach (aligning two potentially huge point clouds and automatic change detection by comparing the reconstructed volumes) and explains in detail the proposed solution.}, author = {Koch, P. and Engelhardt, H. and May, S. and Schmidpeter, M. and Ziegler, J. and {N{\"u}chter}, A.}, booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '20)}, keywords = {author}, month = 11, pages = {1–6}, title = {{Signed Distance Based Reconstruction for Exploration and Change Detection in Underground Mining Disaster Prevention}}, year = 2020 }
• 
  Formations of Small Satellites to Realize Sensor Networks for Earth Observation. Schilling, K.; Nüchter, A. In Proceedings of the 24th IMEKO TC4 International Symposium. The International Measurement Confederation, Palermo, Italy (online), 2020.
  • [ Abstract ]
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  At the level of small satellites with a mass of a few kilograms all capabilities of self-organizing sensor networks for Earth observation can be realized. Photogrammetry methods enable sensor data fusion to generate 3-dimensional images of a target area. Here appropriate satellite position information in combination with attitude determination and control provides precision pointing accuracies to generate suitable input for subsequent data processing. This way, on small satellites efficient methods for distributed sensor systems in orbit can be implemented.

  @inproceedings{IMEKO2020, abstract = {At the level of small satellites with a mass of a few kilograms all capabilities of self-organizing sensor networks for Earth observation can be realized. Photogrammetry methods enable sensor data fusion to generate 3-dimensional images of a target area. Here appropriate satellite position information in combination with attitude determination and control provides precision pointing accuracies to generate suitable input for subsequent data processing. This way, on small satellites efficient methods for distributed sensor systems in orbit can be implemented.}, address = {Palermo, Italy (online)}, author = {Schilling, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the 24th IMEKO TC4 International Symposium}, keywords = {sys:relevantfor:uniwue_cs7}, month = {09}, publisher = {The International Measurement Confederation}, title = {Formations of Small Satellites to Realize Sensor Networks for Earth Observation}, year = 2020 }
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  Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images. Seufert, M.; Kargl, J.; Schauer, J.; Nüchter, A.; Hoßfeld, T. In IEEE 12th International Conference on Quality of Multimedia Experience (QoMEX), pp. 1–6. 2020.
  • [ Abstract ]
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  Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. As the recorded point clouds can be used to render computer-generated images and models, they are of particular interest in the domains of geographical and architectural engineering, as well as for computer graphics (e.g., games or virtual reality). However, point clouds have a huge storage demand, thus, point clouds shall be reduced by removing some of the points. This will inevitably also reduce the Quality of Experience (QoE) of media, which is rendered from the reduced point clouds. In this work, the impact of two different reduction methods on the QoE of rendered images is investigated from two point of views, i.e., based on ratings from both naive crowdworkers as well as point cloud experts.

  @inproceedings{QMEX2020, abstract = {Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. As the recorded point clouds can be used to render computer-generated images and models, they are of particular interest in the domains of geographical and architectural engineering, as well as for computer graphics (e.g., games or virtual reality). However, point clouds have a huge storage demand, thus, point clouds shall be reduced by removing some of the points. This will inevitably also reduce the Quality of Experience (QoE) of media, which is rendered from the reduced point clouds. In this work, the impact of two different reduction methods on the QoE of rendered images is investigated from two point of views, i.e., based on ratings from both naive crowdworkers as well as point cloud experts.}, author = {{Seufert}, M. and {Kargl}, J. and {Schauer}, J. and {N{\"u}chter}, A. and {Hoßfeld}, T.}, booktitle = {IEEE 12th International Conference on Quality of Multimedia Experience (QoMEX)}, keywords = {author}, month = {05}, pages = {1–6}, title = {Different Points of View: Impact of 3D Point Cloud Reduction on QoE of Rendered Images}, year = 2020 }
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  RADLER -- ein Einrad als RADialer LasERscanner. Borrmann, D.; Jörissen, S.; Nüchter, A. In Allgemeine Vermessungs-Nachrichten (AVN), 127(1), pp. 18–27. 2020.
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  Es wird ein modifiziertes Einrad als Träger eines Multisensorsystems vorgestellt, bei dem ein an der Radachse befestigter 2D-Profil-Laserscanner ein radiales 3D-Scanpattern erzeugt. Dieses neuartige, kosten­ günstige Multisensorsystem verbindet die Vorteile von radgetriebenen Plattformen mit denen von Handscannern. Nach der Vorstellung des Hardwareaufbaus und der Sensorintegration werden die Ergebnisse aus vier Testszenarien präsentiert und bewertet.

  @article{AVN2020, abstract = {Es wird ein modifiziertes Einrad als Träger eines Multisensorsystems vorgestellt, bei dem ein an der Radachse befestigter 2D-Profil-Laserscanner ein radiales 3D-Scanpattern erzeugt. Dieses neuartige, kosten­ günstige Multisensorsystem verbindet die Vorteile von radgetriebenen Plattformen mit denen von Handscannern. Nach der Vorstellung des Hardwareaufbaus und der Sensorintegration werden die Ergebnisse aus vier Testszenarien präsentiert und bewertet.}, author = {Borrmann, D. and J{\"o}rissen, S. and N{\"u}chter, A.}, journal = {Allgemeine Vermessungs-Nachrichten (AVN)}, keywords = {sys:relevantfor:uniwue_cs7}, month = {02}, number = 1, pages = {18–27}, title = {{RADLER – ein Einrad als RADialer LasERscanner}}, volume = 127, year = 2020 }

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  A low cost underwater test environment. van der Lucht, J.; Bleier, M.; Nüchter, A. In Proceedings of LowCost 3D 2019, of ISPRS Int. Archieves Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLII-2/W17, pp. 399–404. Strasbourg, France, 2019.
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  In this paper we present the setup of a low cost underwater test environment. The employed materials and structures are described as well as the lessons learned during operations and experiments conducted in the water tank. We provide the bill of materials and a break-down of the costs involved in setting up the test site. The goal was to build a low cost test environment for underwater applications, because our lab is around 40 minutes by car from the nearest lake. Also a natural lake is not an optimal location for first test and experiments, because the access to the water is difficult and logistics of equipment is time consuming. This work aims to describe what experiences we have gained during the time of construction. Which materials we used and what we would do differently next time. Furthermore, we describe the idea and process to place calibration markers inside the container and how the water thwarted our plan. We show that it is possible to realize a useful test environment for underwater experiments for less than Euro 20.000.

  @inproceedings{LC2019, abstract = {In this paper we present the setup of a low cost underwater test environment. The employed materials and structures are described as well as the lessons learned during operations and experiments conducted in the water tank. We provide the bill of materials and a break-down of the costs involved in setting up the test site. The goal was to build a low cost test environment for underwater applications, because our lab is around 40 minutes by car from the nearest lake. Also a natural lake is not an optimal location for first test and experiments, because the access to the water is difficult and logistics of equipment is time consuming. This work aims to describe what experiences we have gained during the time of construction. Which materials we used and what we would do differently next time. Furthermore, we describe the idea and process to place calibration markers inside the container and how the water thwarted our plan. We show that it is possible to realize a useful test environment for underwater experiments for less than Euro 20.000.}, address = {Strasbourg, France}, author = {van der Lucht, J. and Bleier, M. and N{\"u}chter, A.}, booktitle = {Proceedings of LowCost 3D 2019}, keywords = {myown}, month = 11, pages = {399–404}, series = {ISPRS Int. Archieves Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLII-2/W17}, title = {A low cost underwater test environment}, year = 2019 }
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  Imaging the subsurface of planetary volcanic analogues using ambient seismic noise data at the Tinguatón Volcano (Lanzarote, Canary Islands). Torrese, P.; Rossi, A. Pio; Unnithan, V.; Borrmann, D.; Lauterbach, H.; Luzzi, E.; Pozzobon, R.; Sauro, F.; Bessone, L.; Nüchter, A. In Proceedings of the EGU General Assembly 2019, Poster: New mission concepts, enabling technologies and terrestrial analogue studies for planetary explorationn. Vienna, Austria, 2019.
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  @inproceedings{EGU2019, address = {Vienna, Austria}, author = {Torrese, P. and Rossi, A. Pio and Unnithan, V. and Borrmann, D. and Lauterbach, H. and Luzzi, E. and Pozzobon, R. and Sauro, F. and Bessone, L. and N{\"u}chter, A.}, booktitle = {Proceedings of the EGU General Assembly 2019, Poster: New mission concepts, enabling technologies and terrestrial analogue studies for planetary explorationn}, keywords = {myown}, month = {04}, number = {EGU2018-18492}, title = {{Imaging the subsurface of planetary volcanic analogues using ambient seismic noise data at the Tinguatón Volcano (Lanzarote, Canary Islands)}}, year = 2019 }
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  MARC -- Modular Autonomous Adaptable Robot Concept. Edlinger, R.; Nüchter, A. In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’19), pp. 1–7. 2019.
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  The paper introduces a novel modular and adaptable payload concept for plugging in sensor and actuator platforms such as 3D LIDAR and visual sensor systems and robot manipulator and gripper systems. Integration, programming and operation of heterogeneous robot systems (such as mobile manipulators or robots in a machine network) are very complex tasks for plant operators. Heterogeneous system components have to be orchestrated (via proprietary interfaces) by higher-level control systems. Robot programs are created offline, in proprietary tools, and used through macros. System components are generally not compatible and interchangeable across manufacturers. These have to be programmed separately in manufacturer-specific tools. Cross-component debugging is difficult. The operation of complex systems is difficult, requires intensive training, and is currently limited to simple graphical user interfaces (GUI). As part of process optimization, it is usually necessary to optimize process points during the start-up phase. This requires highly skilled personnel capable of robot programming at the plant operators site. The combination of heterogeneous robot modules results in many new hazardous situations. It is therefore necessary to include an appropriate safety concept. The goal is to design a robot payload concept with a plug-and-play approach to be used as a modular and flexible unit. This shall reduce the effort for system integration and sensor calibrating significantly and provide a customized perception of the environment during certain work processes. The modular, autonomous and adaptable robot concept with several sensors and hardware components was implemented as a prototype on a rescue robot. The modules have already been integrated on other autonomous vehicles for exploration and dexterity tasks.

  @inproceedings{SSRR2019_2, abstract = {The paper introduces a novel modular and adaptable payload concept for plugging in sensor and actuator platforms such as 3D LIDAR and visual sensor systems and robot manipulator and gripper systems. Integration, programming and operation of heterogeneous robot systems (such as mobile manipulators or robots in a machine network) are very complex tasks for plant operators. Heterogeneous system components have to be orchestrated (via proprietary interfaces) by higher-level control systems. Robot programs are created offline, in proprietary tools, and used through macros. System components are generally not compatible and interchangeable across manufacturers. These have to be programmed separately in manufacturer-specific tools. Cross-component debugging is difficult. The operation of complex systems is difficult, requires intensive training, and is currently limited to simple graphical user interfaces (GUI). As part of process optimization, it is usually necessary to optimize process points during the start-up phase. This requires highly skilled personnel capable of robot programming at the plant operators site. The combination of heterogeneous robot modules results in many new hazardous situations. It is therefore necessary to include an appropriate safety concept. The goal is to design a robot payload concept with a plug-and-play approach to be used as a modular and flexible unit. This shall reduce the effort for system integration and sensor calibrating significantly and provide a customized perception of the environment during certain work processes. The modular, autonomous and adaptable robot concept with several sensors and hardware components was implemented as a prototype on a rescue robot. The modules have already been integrated on other autonomous vehicles for exploration and dexterity tasks.}, author = {{Edlinger}, R. and {N{\"u}chter}, A.}, booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '19)}, keywords = {myown}, month = {09}, pages = {1–7}, title = {{MARC – Modular Autonomous Adaptable Robot Concept}}, year = 2019 }
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  Korrektur der Brechung an der Wasseroberfläche beim triangulationsbasierten 3D-Laserscannen. van der Lucht, J.; Bleier, M.; Leutert, F.; Schilling, K.; Nüchter, A. In Allgemeine Vermessungs-Nachrichten (AVN), 126, pp. 43–52. 2019.
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  Die vorliegende Arbeit beschäftigt sich mit der Korrektur der Brechung an der Wasseroberfläche beim triangulationsbasierten 3D Laserscannen. Hierzu wurde eine Methode entwickelt, um mit einem Structured Light (SL) System 3D-Daten von teilweise mit Wasser bedeckten Strukturen anzufertigen und die dabei entstehende Brechung an der Wasseroberfläche zu korrigieren. Diese wurde anschließend in einem Versuchsaufbau evaluiert. Der Scanner wurde dabei an einem KUKA KR-16 Manipulatorarm befestigt, um den Scanner gleichmäßig, definiert und wiederholbar zu bewegen. Die Bewegungen des Scanners wurden dabei durch ein externes Trackingsystem erfasst. Ebenfalls wurde bei diesen Versuchen der Einfluss verschiedener Einstrahlwinkel betrachtet. Zu diesem Zweck wurde der Scanner in verschiedenen Winkeln relativ zur Wasseroberfläche positioniert. Durch die entwickelte Methode konnten Fehler durch die Brechung an der Wasseroberfläche erfolgreich korrigiert werden. Außerdem konnte die Lage der Wasseroberfläche ohne externe Markierungen aus den 3D-Daten bestimmt werden.

  @article{AVN2019, abstract = {Die vorliegende Arbeit besch{\"a}ftigt sich mit der Korrektur der Brechung an der Wasseroberfl{\"a}che beim triangulationsbasierten 3D Laserscannen. Hierzu wurde eine Methode entwickelt, um mit einem Structured Light (SL) System 3D-Daten von teilweise mit Wasser bedeckten Strukturen anzufertigen und die dabei entstehende Brechung an der Wasseroberfl{\"a}che zu korrigieren. Diese wurde anschließend in einem Versuchsaufbau evaluiert. Der Scanner wurde dabei an einem KUKA KR-16 Manipulatorarm befestigt, um den Scanner gleichm{\"a}ßig, definiert und wiederholbar zu bewegen. Die Bewegungen des Scanners wurden dabei durch ein externes Trackingsystem erfasst. Ebenfalls wurde bei diesen Versuchen der Einfluss verschiedener Einstrahlwinkel betrachtet. Zu diesem Zweck wurde der Scanner in verschiedenen Winkeln relativ zur Wasseroberfl{\"a}che positioniert. Durch die entwickelte Methode konnten Fehler durch die Brechung an der Wasseroberfl{\"a}che erfolgreich korrigiert werden. Außerdem konnte die Lage der Wasseroberfl{\"a}che ohne externe Markierungen aus den 3D-Daten bestimmt werden.}, author = {van der Lucht, J. and Bleier, M. and Leutert, F. and Schilling, K. and N{\"u}chter, A.}, journal = {Allgemeine Vermessungs-Nachrichten (AVN)}, keywords = {author}, month = {03}, pages = {43–52}, title = {{Korrektur der Brechung an der Wasseroberfl{\"a}che beim triangulationsbasierten 3D-Laserscannen}}, volume = 126, year = 2019 }
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  Position and orientation of sensors for unmanned vehicle systems. Nüchter, A. In Unmanned Vehicle Systems for Geomatics -- Towards Robotic Mapping, P. Patias, C. Armenakis (eds.). Whittles Publishing, 2019.
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  @incollection{Geomatics2019, author = {N{\"u}chter, A.}, booktitle = {Unmanned Vehicle Systems for Geomatics – Towards Robotic Mapping}, editor = {Patias, P. and Armenakis, C.}, keywords = {myown}, publisher = {Whittles Publishing}, title = {Position and orientation of sensors for unmanned vehicle systems}, year = 2019 }
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  Towards an Underwater 3D Laser Scanning System for Mobile Mapping. Bleier, M.; van der Lucht, J.; Nüchter, A. In Proceedings of the IEEE ICRA Workshop on Underwater Robotic Perception (ICRAURP ’19). Montreal, Canada, 2019.
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  Digitizing archaeological or industrial sites on land using standard methods of photogrammetry like 3D modeling from photos or laser scanning is well understood. In contrast, precise underwater surveying with high resolution is still a complex and difficult task. In this paper, we present the development and construction of a structured light underwater laser scanning system and show first results on applying the system for mobile scanning in the water. The laser scanner employs two line lasers to project a cross on the scene. This enables mobile scanning in multiple directions and provides an overlapping scan pattern, which is exploited for trajectory optimization. We describe the image processing, calibration and 3D reconstruction methods used for creating point clouds using the system. In experiments conducted in a towing tank we demonstrate 3D scans captured by rotating the scanner on a robotic joint and first results of mobile scans acquired by moving the scanner through the water along a linear trajectory.

  @inproceedings{ICRAURP2019, abstract = {Digitizing archaeological or industrial sites on land using standard methods of photogrammetry like 3D modeling from photos or laser scanning is well understood. In contrast, precise underwater surveying with high resolution is still a complex and difficult task. In this paper, we present the development and construction of a structured light underwater laser scanning system and show first results on applying the system for mobile scanning in the water. The laser scanner employs two line lasers to project a cross on the scene. This enables mobile scanning in multiple directions and provides an overlapping scan pattern, which is exploited for trajectory optimization. We describe the image processing, calibration and 3D reconstruction methods used for creating point clouds using the system. In experiments conducted in a towing tank we demonstrate 3D scans captured by rotating the scanner on a robotic joint and first results of mobile scans acquired by moving the scanner through the water along a linear trajectory.}, address = {Montreal, Canada}, author = {Bleier, M. and van der Lucht, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE ICRA Workshop on Underwater Robotic Perception (ICRAURP '19)}, keywords = {author}, month = {05}, title = {Towards an Underwater 3D Laser Scanning System for Mobile Mapping}, year = 2019 }
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  Self-calibrated Surface Acquisition for Integrated Positioning Verification in Medical Applications. Jörissen, S.; Bleier, M.; Nüchter, A. In Proceedings of the IS\&T International Symposium on Electronic Imaging Science and Technology, of Electronic Imaging, pp. 353–1. Society for Imaging Science and Technology, San Francisco, CA, USA, 2019.
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  This paper presents a novel approach for a position verification system in medical applications. By replacing the already existing cross line laser projectors with galvo- or MEMS-based projectors and utilizing the surveillance cameras, a self-calibration of the system is performed and surface acquisition for positioning verification is demonstrated. The functionality is shown by analyzing the radii of calibration spheres and determining the quality of the captured surface with respect to a reference model. The paper focuses on the demonstration with one pair of camera and projector but can also be extended to a multi-camera-projector system, as present in treatment rooms. Compared to other systems, this approach does not need external hardware and is thus space and cost efficient.

  @inproceedings{EI2019, abstract = {This paper presents a novel approach for a position verification system in medical applications. By replacing the already existing cross line laser projectors with galvo- or MEMS-based projectors and utilizing the surveillance cameras, a self-calibration of the system is performed and surface acquisition for positioning verification is demonstrated. The functionality is shown by analyzing the radii of calibration spheres and determining the quality of the captured surface with respect to a reference model. The paper focuses on the demonstration with one pair of camera and projector but can also be extended to a multi-camera-projector system, as present in treatment rooms. Compared to other systems, this approach does not need external hardware and is thus space and cost efficient.}, address = {San Francisco, CA, USA}, author = {J{\"o}rissen, S. and Bleier, M. and N{\"u}chter, A.}, booktitle = {Proceedings of the IS\&T International Symposium on Electronic Imaging Science and Technology}, keywords = {myown}, month = {01}, pages = {353-1–353-8}, publisher = {Society for Imaging Science and Technology}, series = {Electronic Imaging}, title = {{Self-calibrated Surface Acquisition for Integrated Positioning Verification in Medical Applications}}, year = 2019 }
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  Technical Report: Reduction and Compression using Octrees --- 3DTK’s entry to the ICIP 2019 Challenge on Point Cloud Coding. Nüchter, A.; Schauer, J.; Borrmann, D. Robotics and Telematics, University of Würzburg, Würzburg, Germany, 2019.
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  Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. Several mechanisms are available in literature for storing and compressing point clouds, e.g., applying conventional image based compression methods to 3D point clouds. In this challenge entry however, we make use of octree subsampling and compression, which is nicely suited for unstructured, registered 3D point clouds of arbitrarily shaped objects.

  @techreport{ICIP2019, abstract = {Modern photogrammetric methods as well as laser measurement systems make it easy to collect large 3D point clouds that sample objects or environments. Several mechanisms are available in literature for storing and compressing point clouds, e.g., applying conventional image based compression methods to 3D point clouds. In this challenge entry however, we make use of octree subsampling and compression, which is nicely suited for unstructured, registered 3D point clouds of arbitrarily shaped objects.}, address = {Würzburg, Germany}, author = {N{\"u}chter, A. and Schauer, J. and Borrmann, D.}, institution = {Robotics and Telematics, University of Würzburg}, keywords = {sys:relevantfor:uniwue_cs7}, month = {09}, title = {{Technical Report: Reduction and Compression using Octrees — {3DTK}'s entry to the {ICIP} 2019 Challenge on Point Cloud Coding}}, year = 2019 }
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  3D UNDERWATER MINE MODELLING IN THE VAMOS PROJECT. Bleier, M.; Almeida, C.; Ferreira, A.; Pereira, R.; Matias, B.; Almeida, J.; Pidgeon, J.; van der Lucht, J.; Schilling, K.; Martins, A.; Silva, E.; Nüchter, A. In Proceedings of the 2nd ISPRS International Workshop Underwater 3D Recording \& Modelling: A tool for modern applications and CH recording, of ISPRS Archives Photogrammetry and Remote Senssing Spatial Information Science, Volume XLII-2/W10, pp. 105–112. Limassol, Cyprus, 2019.
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  The project Viable Alternative Mine Operating System (VAMOS) develops a novel underwater mining technique for extracting inland mineral deposits in flooded open-cut mines. From a floating launch and recovery vessel a remotely-operated underwater mining vehicle with a roadheader cutting machine is deployed. The cut material is transported to the surface via a flexible riser hose. Since there is no direct intervisibility between the operator and the mining machine, the data of the sensor systems can only be perceived via a computer interface. Therefore, part of the efforts in the project focus on enhancing the situational awareness of the operator by providing a 3D model of the mine combined with representations of the mining equipment and sensor data. We present a method how a positioning and navigation system, perception system and mapping system can be used to create a replica of the physical system and mine environment in Virtual Reality (VR) in order to assist remote control. This approach is beneficial because it allows visualizing different sensor information and data in a consistent interface, and enables showing the complete context of the mining site even if only part of the mine is currently observed by surveying equipment. We demonstrate how the system is used during tele-operation and show results achieved during the field trials of the complete system in Silvermines, Ireland.

  @inproceedings{ISPRS_3DUW, abstract = {The project Viable Alternative Mine Operating System (VAMOS) develops a novel underwater mining technique for extracting inland mineral deposits in flooded open-cut mines. From a floating launch and recovery vessel a remotely-operated underwater mining vehicle with a roadheader cutting machine is deployed. The cut material is transported to the surface via a flexible riser hose. Since there is no direct intervisibility between the operator and the mining machine, the data of the sensor systems can only be perceived via a computer interface. Therefore, part of the efforts in the project focus on enhancing the situational awareness of the operator by providing a 3D model of the mine combined with representations of the mining equipment and sensor data. We present a method how a positioning and navigation system, perception system and mapping system can be used to create a replica of the physical system and mine environment in Virtual Reality (VR) in order to assist remote control. This approach is beneficial because it allows visualizing different sensor information and data in a consistent interface, and enables showing the complete context of the mining site even if only part of the mine is currently observed by surveying equipment. We demonstrate how the system is used during tele-operation and show results achieved during the field trials of the complete system in Silvermines, Ireland.}, address = {Limassol, Cyprus}, author = {Bleier, M. and Almeida, C. and Ferreira, A. and Pereira, R. and Matias, B. and Almeida, J. and Pidgeon, J. and van der Lucht, J. and Schilling, K. and Martins, A. and Silva, E. and N{\"u}chter, A.}, booktitle = {Proceedings of the 2nd ISPRS International Workshop Underwater 3D Recording \& Modelling: A tool for modern applications and CH recording}, keywords = {myown}, month = {05}, pages = {105–112}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Information Science, Volume XLII-2/W10}, title = {{3D UNDERWATER MINE MODELLING IN THE VAMOS PROJECT}}, year = 2019 }
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  The Eins3D Project -- Instantaneous UAV-Based 3D Mapping for Search and Rescue Applications. Lauterbach, H. A.; Koch, C. B.; Hess, R.; Eck, D.; Schilling, K.; Nüchter, A. In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’19), pp. 1–6. 2019.
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  The overview of a situation in a search and rescue disaster is the key aspect of an effective assistance. In the recent years the utilization of multicopter with various photogrammetry systems is an upcoming trend and an open field of research. This paper discusses the technical aspects of an automated integral system that will support rescuers during the strategic mission planning and will give situational awareness by instantaneous 3D mapping. The approach combines sensors including a 3D Laserscanner, a thermal camera and an attitude system as a payload unit on an Multicopter. The continuous data fusion and the down link are providing an instant 3D environment map that is continuously revised and updated.

  @inproceedings{SSRR2019_1, abstract = {The overview of a situation in a search and rescue disaster is the key aspect of an effective assistance. In the recent years the utilization of multicopter with various photogrammetry systems is an upcoming trend and an open field of research. This paper discusses the technical aspects of an automated integral system that will support rescuers during the strategic mission planning and will give situational awareness by instantaneous 3D mapping. The approach combines sensors including a 3D Laserscanner, a thermal camera and an attitude system as a payload unit on an Multicopter. The continuous data fusion and the down link are providing an instant 3D environment map that is continuously revised and updated.}, author = {{Lauterbach}, H. A. and {Koch}, C. B. and {Hess}, R. and {Eck}, D. and {Schilling}, K. and {N{\"u}chter}, A.}, booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '19)}, keywords = {sys:relevantfor:uniwue_cs7}, month = {09}, pages = {1–6}, title = {{The Eins3D Project – Instantaneous UAV-Based 3D Mapping for Search and Rescue Applications}}, year = 2019 }
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  Projection based dynamic point cloud compression using 3DTK toolkit and H.265/HEVC. Dumic, E.; Bjelopera, A.; Nüchter, A. In Proceedings of the 2nd International Colloquium on Smart Grid Metrology (SMAGRIMET’’19), pp. 1–4. IEEE Xplore, Split, Croatia, 2019.
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  This paper presents novel compression method for dynamic point clouds based on projections and the H.265/HEVC video coder. We used 3DTK - The 3D Toolkit to create equirect-angular projection images and x265 as H.265/HEVC coder, to compress and extract created projection images. Compression was introduced in 3DTK generated projection image size (differ-ent pixel size, but compatible with later video compression), as well as lossless/lossy video compression. Visual inspection shows better results for compression only using different projection resolution, with lossless video compression. Lossy video compression adds noise and creates additional points, resulting in lower visual quality.

  @inproceedings{SMGM_2019, abstract = {This paper presents novel compression method for dynamic point clouds based on projections and the H.265/HEVC video coder. We used 3DTK - The 3D Toolkit to create equirect-angular projection images and x265 as H.265/HEVC coder, to compress and extract created projection images. Compression was introduced in 3DTK generated projection image size (differ-ent pixel size, but compatible with later video compression), as well as lossless/lossy video compression. Visual inspection shows better results for compression only using different projection resolution, with lossless video compression. Lossy video compression adds noise and creates additional points, resulting in lower visual quality.}, address = {Split, Croatia}, author = {{Dumic}, E. and {Bjelopera}, A. and {N{\"u}chter}, A.}, booktitle = {Proceedings of the 2nd International Colloquium on Smart Grid Metrology (SMAGRIMET''19)}, keywords = {myown}, month = {04}, pages = {1–4}, publisher = {IEEE Xplore}, title = {{Projection based dynamic point cloud compression using 3DTK toolkit and H.265/HEVC}}, year = 2019 }
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  Signed Distance Based Reconstruction for Exploration and Change Detection in Underground Mining Disaster Prevention. Koch, P.; May, S.; Engelhardt, H.; Ziegler, J.; Nüchter, A. In IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’19), pp. 1–2. 2019.
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  This publication describes an application of a Truncated Signed Distance Mapping approach for disaster intervention in underground mine shafts through geometrical change detection of the shaft walls. The paper describes two main problems of such an approach (aligning two potentially huge point clouds and automatic change detection by comparing the reconstructed volumes) and explains in detail the proposed solution.

  @inproceedings{SSRR2019_3, abstract = {This publication describes an application of a Truncated Signed Distance Mapping approach for disaster intervention in underground mine shafts through geometrical change detection of the shaft walls. The paper describes two main problems of such an approach (aligning two potentially huge point clouds and automatic change detection by comparing the reconstructed volumes) and explains in detail the proposed solution.}, author = {{Koch}, P. and {May}, S. and {Engelhardt}, H. and {Ziegler}, J. and {N{\"u}chter}, A.}, booktitle = {IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '19)}, keywords = {myown}, month = {09}, pages = {1–2}, title = {{Signed Distance Based Reconstruction for Exploration and Change Detection in Underground Mining Disaster Prevention}}, year = 2019 }
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  RADLER -- Ein Einrad als RADialer LasER Scanner. Borrmann, D.; Jörissen, S.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2019, Jade Hochschule, pp. 12–21. 2019.
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  Die Weiterentwicklung in der 3D-Messtechnik hat in den letzten Jahren eine Vielzahl an unterschiedlichen Messgeräten zu 3D-Umgebungserfassung hervorgebracht, jedes davon mit seinen eigenen Vorzügen und Schwächen. Diese Arbeit stellt ein modifiziertes Einrad vor, bei dem ein an der Radachse befestigter 2D Laserscanner ein radiales 3D Scanpattern erzeugt. Dieses neuartige, kostengünstige Messgerät verbindet die Vorteile von radgetriebenen Scangeräten mit denen von Handscannern. Nach der Vorstellung des Hardwareaufbaus und der Sensorintegration werden die Ergebnisse anhand von drei Testszenarien ausgewertet und mit den Daten eines terrestrischen 3D-Laserscanners verglichen.

  @inproceedings{3DTAGE2019, abstract = {Die Weiterentwicklung in der 3D-Messtechnik hat in den letzten Jahren eine Vielzahl an unterschiedlichen Messgeräten zu 3D-Umgebungserfassung hervorgebracht, jedes davon mit seinen eigenen Vorzügen und Schwächen. Diese Arbeit stellt ein modifiziertes Einrad vor, bei dem ein an der Radachse befestigter 2D Laserscanner ein radiales 3D Scanpattern erzeugt. Dieses neuartige, kostengünstige Messgerät verbindet die Vorteile von radgetriebenen Scangeräten mit denen von Handscannern. Nach der Vorstellung des Hardwareaufbaus und der Sensorintegration werden die Ergebnisse anhand von drei Testszenarien ausgewertet und mit den Daten eines terrestrischen 3D-Laserscanners verglichen.}, author = {Borrmann, D. and J{\"o}rissen, S. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2019, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {12–21}, title = {{RADLER – Ein Einrad als RADialer LasER Scanner}}, year = 2019 }
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  The Golden Bullet: A Comparative Study for Target Acquisition, Pointing and Shooting. Heydn, K. A. M.; Dietrich, M. P.; Barkowsky, M.; Winterfeldt, G.; von Mammen, S.; Nüchter, A. In 11th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games ’19), pp. 1–8. 2019.
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  In this study, we evaluate an interaction sequence performed by six modalities consisting of desktop-based (DB) and virtual reality (VR) environments using different input devices. For the given study, we implemented a vertical prototype of a first person shooter (FPS) game scenario, focusing on the genre-defining point-and-shoot mechanic. We introduce measures to evaluate the success of the according interaction sequence (times for target acquisition, pointing, shooting, overall net time, and number of shots) and conduct experiments to record and compare the users' performances. We show that interacting using head-tracking for landscape-rotation is performing similarly to the input of a screen-centered mouse and also yielded shortest times in target acquisition and pointing. Although using head-tracking for target acquisition and pointing was most efficient, subjects rated the modality using head-tracking for target acquisition and a 3DOF Controller for pointing best. Eye-tracking (ET) yields promising results, but calibration issues need to be resolved to enhance reliability and overall user experience.

  @inproceedings{VSGAMES2019, abstract = {In this study, we evaluate an interaction sequence performed by six modalities consisting of desktop-based (DB) and virtual reality (VR) environments using different input devices. For the given study, we implemented a vertical prototype of a first person shooter (FPS) game scenario, focusing on the genre-defining point-and-shoot mechanic. We introduce measures to evaluate the success of the according interaction sequence (times for target acquisition, pointing, shooting, overall net time, and number of shots) and conduct experiments to record and compare the users' performances. We show that interacting using head-tracking for landscape-rotation is performing similarly to the input of a screen-centered mouse and also yielded shortest times in target acquisition and pointing. Although using head-tracking for target acquisition and pointing was most efficient, subjects rated the modality using head-tracking for target acquisition and a 3DOF Controller for pointing best. Eye-tracking (ET) yields promising results, but calibration issues need to be resolved to enhance reliability and overall user experience.}, author = {{Heydn}, K. A. M. and {Dietrich}, M. P. and {Barkowsky}, M. and {Winterfeldt}, G. and {von Mammen}, S. and {N{\"u}chter}, A.}, booktitle = {11th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games '19)}, keywords = {myown}, month = {09}, pages = {1–8}, title = {The Golden Bullet: A Comparative Study for Target Acquisition, Pointing and Shooting}, year = 2019 }
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  Mobile mapping of the La Corona lavatube on Lanzarote. Lauterbach, H. A.; Borrmann, D.; Nüchter, A.; Rossi, A. P.; Unnithan, V.; Torrese, P.; Pozzobon, R. In Proceedings of the ISPRS Geospatial Week 2019, Laserscanning 2019, of ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., IV-2/W5, pp. 381–387. Enschede, Netherlands, 2019.
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  Planetary surfaces consist of rough terrain and cave-like environments. Future planetary exploration demands for accurate mapping. However, recent backpack mobile mapping systems are mostly tested in structured, indoor environments. This paper evaluates the use of a backpack mobile mapping system in a cave-like environment. The experiments demonstrate the abilities of an continuous-time optimization approach by mapping part of a lavatube of the La Corona volcano system on Lanzarote. We compare two strategies for trajectory estimation relying either on 2D or 3D laser scanners and show that a 3D laser scanner substantially improved the final results.

  @inproceedings{LS2019, abstract = {Planetary surfaces consist of rough terrain and cave-like environments. Future planetary exploration demands for accurate mapping. However, recent backpack mobile mapping systems are mostly tested in structured, indoor environments. This paper evaluates the use of a backpack mobile mapping system in a cave-like environment. The experiments demonstrate the abilities of an continuous-time optimization approach by mapping part of a lavatube of the La Corona volcano system on Lanzarote. We compare two strategies for trajectory estimation relying either on 2D or 3D laser scanners and show that a 3D laser scanner substantially improved the final results.}, address = {Enschede, Netherlands}, author = {Lauterbach, H. A. and Borrmann, D. and N{\"u}chter, A. and Rossi, A. P. and Unnithan, V. and Torrese, P. and Pozzobon, R.}, booktitle = {Proceedings of the ISPRS Geospatial Week 2019, Laserscanning 2019}, keywords = {myown}, month = {06}, pages = {381–387}, series = {ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., IV-2/W5}, title = {Mobile mapping of the La Corona lavatube on Lanzarote}, year = 2019 }
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  Satellite Technology: An international, interdisciplinary master program with focus on hands-on experiences. Schilling, K.; Nüchter, A.; Montenegro, S. In Proceedings 70th International Astronautical Congress. Washington D.C., USA, 2019.
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  Within the spacecraft engineering programs at Bachelor, Master and PhD level University Wuerzburg started 2018 the new program Satellite Technology. As main progress in modern spacecraft engineering focusses on advanced electronics and software, this program is realized within the Computer Science Institute. Specific emphasis is on modern microelectronic and data processing systems onboard the satellites, as well as algorithmic aspects in the application sectors related to Earth observation, telecommunication and scientific exploration. Specific emphasis is on hands-on experiences by the design of FloatSats, CanSats and educational CubeSats in order to complement lectures by practical implementation aspects. The students are offered excursions to space research institutes (DLR, Fraunhofer, Max-Planck institutes) and to industry (Airbus Space, OHB,...). In the breacks between lecture periods they get offered opportunities to participate in one of the ongoing satellite reallization projects. As there are currently 18 small satellites implemented in Wuerzburg there are excellent opportunities for interesting hands-on experiences. In 'Satellite Technology' 12 Bavarian partners (Universities, research institutes and industry) addressing space applications cooperate within the Elitenetzwerk Bayern to offer to the students in English language a program with emphasis on small satellite design aspects. In addition the most relevant application fields in Earth observation and in telecommunication are well represented in the program. International partner universities are integrated to allow the students to include related study segments abroad into the curricullum, in particular for Master thesis work. This contribution adresses the international university cooperation, the contents of the curriculum, as well as the specific challenges and experiences acquired in setting up this international program.

  @inproceedings{IAC2019, abstract = {Within the spacecraft engineering programs at Bachelor, Master and PhD level University Wuerzburg started 2018 the new program Satellite Technology. As main progress in modern spacecraft engineering focusses on advanced electronics and software, this program is realized within the Computer Science Institute. Specific emphasis is on modern microelectronic and data processing systems onboard the satellites, as well as algorithmic aspects in the application sectors related to Earth observation, telecommunication and scientific exploration. Specific emphasis is on hands-on experiences by the design of FloatSats, CanSats and educational CubeSats in order to complement lectures by practical implementation aspects. The students are offered excursions to space research institutes (DLR, Fraunhofer, Max-Planck institutes) and to industry (Airbus Space, OHB,...). In the breacks between lecture periods they get offered opportunities to participate in one of the ongoing satellite reallization projects. As there are currently 18 small satellites implemented in Wuerzburg there are excellent opportunities for interesting hands-on experiences. In 'Satellite Technology' 12 Bavarian partners (Universities, research institutes and industry) addressing space applications cooperate within the Elitenetzwerk Bayern to offer to the students in English language a program with emphasis on small satellite design aspects. In addition the most relevant application fields in Earth observation and in telecommunication are well represented in the program. International partner universities are integrated to allow the students to include related study segments abroad into the curricullum, in particular for Master thesis work. This contribution adresses the international university cooperation, the contents of the curriculum, as well as the specific challenges and experiences acquired in setting up this international program.}, address = {Washington D.C., USA}, author = {Schilling, K. and N{\"u}chter, A. and Montenegro, S.}, booktitle = {Proceedings 70th International Astronautical Congress}, keywords = {sys:relevantfor:uniwue_cs7}, month = 10, number = {IAC-19 E1.4.54918}, title = {Satellite Technology: An international, interdisciplinary master program with focus on hands-on experiences}, year = 2019 }
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  SCOUT3D -- An underwater laser scanning system for mobile mapping. Bleier, M.; v.d. Lucht, J.; Nüchter, A. In Proceedings of Optical 3D Metrology 2019, of ISPRS Int. Archieves Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLII-2/W18, pp. 13–18. Strasbourg, France, 2019.
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  This paper presents an underwater laser scanning system and GNSS based trajectory estimation system for scanning from a surface vessle in shallow water. The system has an above-the-water and an underwater component. Above-the-water two low-cost multi- band GNSS receivers with an antenna baseline of one meter are used for RTK positioning with heading. The full 6-DOF is estimated by fusing the satellite navigation data with a MEMS-based INS. The 3D data is captured in water using a structured light scanner consisting of a low-light underwater camera and a green cross line laser projector. We describe the development of the system and employed hardware components. We show results of scanning a large test object in a water tank acquired by from a tripod with a motorized yaw axis. Additionally, we demonstrate first results of mobile mapping from a floating platform. We evaluate the performance of the system by measuring the 6-DOF trajectory with an external optical tracking system. Additionally, we assess the quality of the created point cloud using reference objects placed in the scene.

  @inproceedings{O3DM2019, abstract = {This paper presents an underwater laser scanning system and GNSS based trajectory estimation system for scanning from a surface vessle in shallow water. The system has an above-the-water and an underwater component. Above-the-water two low-cost multi- band GNSS receivers with an antenna baseline of one meter are used for RTK positioning with heading. The full 6-DOF is estimated by fusing the satellite navigation data with a MEMS-based INS. The 3D data is captured in water using a structured light scanner consisting of a low-light underwater camera and a green cross line laser projector. We describe the development of the system and employed hardware components. We show results of scanning a large test object in a water tank acquired by from a tripod with a motorized yaw axis. Additionally, we demonstrate first results of mobile mapping from a floating platform. We evaluate the performance of the system by measuring the 6-DOF trajectory with an external optical tracking system. Additionally, we assess the quality of the created point cloud using reference objects placed in the scene.}, address = {Strasbourg, France}, author = {Bleier, M. and v.d. Lucht, J. and N{\"u}chter, A.}, booktitle = {Proceedings of Optical 3D Metrology 2019}, keywords = {author}, month = 11, pages = {13–18}, series = {ISPRS Int. Archieves Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLII-2/W18}, title = {SCOUT3D – An underwater laser scanning system for mobile mapping}, year = 2019 }

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  Structured-light based 3D laser scanning of semi-submerged structures. van der Lucht, J.; Bleier, M.; Leutert, F.; Schilling, K.; Nüchter, A. In Proceedings of the Technical Commision II Mid-term Symposium ``Towards Photogrammetry 2020’’, of ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., IV-2, pp. 287–294. Riva del Garda, Italy, 2018.
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  In this work we look at 3D acquisition of semi-submerged structures with a triangulation based underwater laser scanning system. The motivation is that we want to simultaneously capture data above and below water to create a consistent model without any gaps. The employed structured light scanner consist of a machine vision camera and a green line laser. In order to reconstruct precise surface models of the object it is necessary to model and correct for the refraction of the laser line and camera rays at the water-air boundary. We derive a geometric model for the refraction at the air-water interface and propose a method for correcting the scans. Furthermore, we show how the water surface is directly estimated from sensor data. The approach is verified using scans captured with an industrial manipulator to achieve reproducable scanner trajectories with different incident angles. We show that the proposed method is effective for refractive correction and that it can be applied directly to the raw sensor data without requiring any external markers or targets.

  @inproceedings{COMMII2018, abstract = {In this work we look at 3D acquisition of semi-submerged structures with a triangulation based underwater laser scanning system. The motivation is that we want to simultaneously capture data above and below water to create a consistent model without any gaps. The employed structured light scanner consist of a machine vision camera and a green line laser. In order to reconstruct precise surface models of the object it is necessary to model and correct for the refraction of the laser line and camera rays at the water-air boundary. We derive a geometric model for the refraction at the air-water interface and propose a method for correcting the scans. Furthermore, we show how the water surface is directly estimated from sensor data. The approach is verified using scans captured with an industrial manipulator to achieve reproducable scanner trajectories with different incident angles. We show that the proposed method is effective for refractive correction and that it can be applied directly to the raw sensor data without requiring any external markers or targets.}, address = {Riva del Garda, Italy}, author = {van der Lucht, J. and Bleier, M. and Leutert, F. and Schilling, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the Technical Commision II Mid-term Symposium ``Towards Photogrammetry 2020''}, keywords = {myown}, month = {06}, pages = {287–294}, series = {ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., IV-2}, title = {{Structured-light based 3D laser scanning of semi-submerged structures}}, year = 2018 }
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  Removing non-static objects from 3D laser scan data. Schauer, Johannes; Nüchter, Andreas. In ISPRS Journal of Photogrammetry and Remote Sensing (JPRS), 143, pp. 15–38. 2018.
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  For the purpose of visualization and further post-processing of 3D point cloud data, it is often desirable to remove moving objects from a given data set. Common examples for these moving objects are pedestrians, bicycles and motor vehicles in outdoor scans or manufactured goods and employees in indoor scans of factories. We present a new change detection method which is able to partition the points of multiple registered 3D scans into two sets: points belonging to stationary (static) objects and points belonging to moving (dynamic) objects. Our approach does not require any object detection or tracking the movement of objects over time. Instead, we traverse a voxel grid to find differences in volumetric occupancy for “explicit” change detection. Our main contribution is the introduction of the concept of “point shadows” and how to efficiently compute them. Without them, using voxel grids for explicit change detection is known to suffer from a high number of false positives when applied to terrestrial scan data. Our solution achieves similar quantitative results in terms of F1-score as competing methods while at the same time being faster.

  @article{JPRS_2018, abstract = {For the purpose of visualization and further post-processing of 3D point cloud data, it is often desirable to remove moving objects from a given data set. Common examples for these moving objects are pedestrians, bicycles and motor vehicles in outdoor scans or manufactured goods and employees in indoor scans of factories. We present a new change detection method which is able to partition the points of multiple registered 3D scans into two sets: points belonging to stationary (static) objects and points belonging to moving (dynamic) objects. Our approach does not require any object detection or tracking the movement of objects over time. Instead, we traverse a voxel grid to find differences in volumetric occupancy for “explicit” change detection. Our main contribution is the introduction of the concept of “point shadows” and how to efficiently compute them. Without them, using voxel grids for explicit change detection is known to suffer from a high number of false positives when applied to terrestrial scan data. Our solution achieves similar quantitative results in terms of F1-score as competing methods while at the same time being faster.}, author = {Schauer, Johannes and N{\"u}chter, Andreas}, journal = {ISPRS Journal of Photogrammetry and Remote Sensing (JPRS)}, keywords = {myown}, pages = {15–38}, title = {Removing non-static objects from 3D laser scan data}, volume = 143, year = 2018 }
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  The Peopleremover --- Removing Dynamic Objects From 3-D Point Cloud Data by Traversing a Voxel Occupancy Grid. Schauer, J.; Nüchter, A. In IEEE Robotics and Automation Letters (RAL), 3(3), pp. 1679–1686. 2018.
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  Even though it would be desirable for most postprocessing purposes to obtain a point cloud without moving objects in it, it is often impractical or downright impossible to free a scene from all nonstatic clutter. Outdoor environments contain pedestrians, bicycles, and motor vehicles which cannot easily be stopped from entering the sensor range and indoor environments like factory production lines cannot be evacuated due to production losses during the time of the scan. In this letter, we present a solution to this problem that we call the "peopleremover." Given a registered set of 3-D point clouds, we build a regular voxel occupancy grid and then traverse it along the lines of sight between the sensor and the measured points to find the differences in volumetric occupancy between the scans. Our approach works for scan slices from mobile mapping as well as for the more general scenario of terrestrial scan data. The result is a clean point cloud free of dynamic objects.

  @article{ICRA2018, abstract = {Even though it would be desirable for most postprocessing purposes to obtain a point cloud without moving objects in it, it is often impractical or downright impossible to free a scene from all nonstatic clutter. Outdoor environments contain pedestrians, bicycles, and motor vehicles which cannot easily be stopped from entering the sensor range and indoor environments like factory production lines cannot be evacuated due to production losses during the time of the scan. In this letter, we present a solution to this problem that we call the "peopleremover." Given a registered set of 3-D point clouds, we build a regular voxel occupancy grid and then traverse it along the lines of sight between the sensor and the measured points to find the differences in volumetric occupancy between the scans. Our approach works for scan slices from mobile mapping as well as for the more general scenario of terrestrial scan data. The result is a clean point cloud free of dynamic objects.}, author = {Schauer, J. and N{\"u}chter, A.}, journal = {IEEE Robotics and Automation Letters (RAL)}, keywords = {myown}, month = {07}, number = 3, pages = {1679–1686}, title = {{{The Peopleremover — Removing Dynamic Objects From 3-D Point Cloud Data by Traversing a Voxel Occupancy Grid}}}, volume = 3, year = 2018 }
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  Korrektur der Brechung an der Wasseroberfläche beim triangulationsbasierten 3D-Laserscannen. van der Lucht, J.; Bleier, M.; Leutert, F.; Schilling, K.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2018, Jade Hochschule, pp. 87–102. 2018.
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  Die vorliegende Arbeit beschäftigt sich mit der Korrektur der Brechung an der Wasseroberfläche beim triangulationsbasierten 3D Laserscannen. Hierzu wurde eine Methode entwickelt, die es ermöglicht, mit einem Structured Light (SL) System 3D-Daten von teilweise mit Wasser bedeckten Strukturen anzufertigen und die dabei entstehende Brechung an der Wasseroberfläche zu korrigieren. Diese wurde anschließend in einem Versuchsaufbau evaluiert. Der Scanner wurde dabei an einem KUKA KR-16 Manipulatorarm befestigt, was die Möglichkeit bietet den Scanner gleichmäßig, definiert und wiederholbar zu bewegen. Die Bewegungen des Scanners wurden dabei durch ein externes Trackingsystem erfasst. Ebenfalls wurde bei diesen Versuchen der Einfluss verschiedener Einstrahlwinkel betrachtet. Zu diesem Zweck wurde der Scanner in verschiedenen Winkeln relativ zur Wasseroberfläche bewegt. Durch die entwickelte Methode konnten Fehler durch die Brechung an der Wasseroberfläche erfolgreich korrigiert werden. Außerdem konnte die Lage der Wasseroberfläche ohne externe Markierungen aus den 3D-Daten bestimmt werden.

  @inproceedings{3DTAGE2018, abstract = {Die vorliegende Arbeit beschäftigt sich mit der Korrektur der Brechung an der Wasseroberfläche beim triangulationsbasierten 3D Laserscannen. Hierzu wurde eine Methode entwickelt, die es ermöglicht, mit einem Structured Light (SL) System 3D-Daten von teilweise mit Wasser bedeckten Strukturen anzufertigen und die dabei entstehende Brechung an der Wasseroberfläche zu korrigieren. Diese wurde anschließend in einem Versuchsaufbau evaluiert. Der Scanner wurde dabei an einem KUKA KR-16 Manipulatorarm befestigt, was die Möglichkeit bietet den Scanner gleichmäßig, definiert und wiederholbar zu bewegen. Die Bewegungen des Scanners wurden dabei durch ein externes Trackingsystem erfasst. Ebenfalls wurde bei diesen Versuchen der Einfluss verschiedener Einstrahlwinkel betrachtet. Zu diesem Zweck wurde der Scanner in verschiedenen Winkeln relativ zur Wasseroberfläche bewegt. Durch die entwickelte Methode konnten Fehler durch die Brechung an der Wasseroberfläche erfolgreich korrigiert werden. Außerdem konnte die Lage der Wasseroberfläche ohne externe Markierungen aus den 3D-Daten bestimmt werden.}, author = {van der Lucht, J. and Bleier, M. and Leutert, F. and Schilling, K. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2018, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {87–102}, title = {{Korrektur der Brechung an der Wasseroberfl{\"a}che beim triangulationsbasierten 3D-Laserscannen}}, year = 2018 }
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  RADLER - A RADial LasER scanning device. Borrmann, D.; Jörissen, S.; Nüchter, A. In Proceedings of the 16th International Symposium of Experimental Robotics (ISER ’18), of Springer Tracts in Advanced Robotics, pp. 655–664. Buenos Aires, Argentina, 2018.
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  Mobile scanning, i.e., the practice of mounting laser scanners on moving platforms is an efficient way to acquire accurate and dense 3D point clouds of outdoor environments for urban and regional planning and architecture. The mobile scenario puts high requirements on the accuracy of the calibration of the measurement system, as small calibration inaccuracies lead to large errors in the resulting point cloud. We propose a novel algorithm for the calibration of a mobile scanning system that estimates the calibration parameters for all sensor components simultaneously without relying on additional hardware. We evaluate the calibration algorithm on several real world data sets where ground truth is available via an accurate geodetic model.

  @inproceedings{ISER2018, abstract = {Mobile scanning, i.e., the practice of mounting laser scanners on moving platforms is an efficient way to acquire accurate and dense 3D point clouds of outdoor environments for urban and regional planning and architecture. The mobile scenario puts high requirements on the accuracy of the calibration of the measurement system, as small calibration inaccuracies lead to large errors in the resulting point cloud. We propose a novel algorithm for the calibration of a mobile scanning system that estimates the calibration parameters for all sensor components simultaneously without relying on additional hardware. We evaluate the calibration algorithm on several real world data sets where ground truth is available via an accurate geodetic model.}, address = {Buenos Aires, Argentina}, author = {Borrmann, D. and J{\"o}rissen, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the 16th International Symposium of Experimental Robotics (ISER '18)}, keywords = {myown}, month = 11, pages = {655-664}, series = {Springer Tracts in Advanced Robotics}, title = {{RADLER - A RADial LasER scanning device}}, year = 2018 }
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  Preliminary Results on Instantaneous UAV-Based 3D Mapping for Rescue Applications. Lauterbach, H. A.; Nüchter, A. In Proceedings of the 16th IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’18), pp. 1–2. Philadelphia, PA, USA, 2018.
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  This report presents a novel approach to generate a 3D map with an UAV while flying over a disaster scene with the aim to present the map instantaneously to the operator and the rescue workers. Our approach extends the well-known ICP algorithm.

  @inproceedings{lauterbach2018preliminary, abstract = {This report presents a novel approach to generate a 3D map with an UAV while flying over a disaster scene with the aim to present the map instantaneously to the operator and the rescue workers. Our approach extends the well-known ICP algorithm.}, address = {Philadelphia, PA, USA}, author = {Lauterbach, H. A. and N{\"u}chter, A.}, booktitle = {Proceedings of the 16th IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '18)}, keywords = {author}, month = {08}, pages = {1–2}, title = {{Preliminary Results on Instantaneous UAV-Based 3D Mapping for Rescue Applications}}, year = 2018 }
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  Positioning. Navigation and Awareness of the !VAMOS! Underwater Robotic Mining System. Almeida, J.; Martins, A.; Almeida, C.; Dias, A.; Matias, B.; Ferreira, A.; Jorge, P.; Martins, R.; Bleier, M.; Nüchter, A.; Pidgeon, J.; Kapusniak, S.; Silva, E. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’18), pp. 1527–1533. 2018.
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  This paper presents the positioning, navigation and awareness (PNA) system developed for the Underwater Robotic Mining System of the !VAMOS! project [1]. It describes the main components of the !VAMOS! system, the PNA sensors in each of those components, the global architecture of the PNA system, and its main subsystems: Position and Navigation, Realtime Mine Modeling, 3D Virtual reality HMI and Real-time grade system. General results and lessons learn during the first mining field trial in Lee Moor, Devon, UK during the months of September and October 2017 are presented.

  @inproceedings{IROS2018, abstract = {This paper presents the positioning, navigation and awareness (PNA) system developed for the Underwater Robotic Mining System of the !VAMOS! project [1]. It describes the main components of the !VAMOS! system, the PNA sensors in each of those components, the global architecture of the PNA system, and its main subsystems: Position and Navigation, Realtime Mine Modeling, 3D Virtual reality HMI and Real-time grade system. General results and lessons learn during the first mining field trial in Lee Moor, Devon, UK during the months of September and October 2017 are presented.}, author = {Almeida, J. and Martins, A. and Almeida, C. and Dias, A. and Matias, B. and Ferreira, A. and Jorge, P. and Martins, R. and Bleier, M. and N{\"u}chter, A. and Pidgeon, J. and Kapusniak, S. and Silva, E.}, booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '18)}, keywords = {myown}, pages = {1527–1533}, title = {{Positioning. Navigation and Awareness of the !VAMOS! Underwater Robotic Mining System}}, year = 2018 }
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  TOM: A formation for photogrammetric earth observation by three cubesats. Schilling, K.; Tzschichholz, T.; Motroniuk, I.; Aumann, A.; Mammadov, I.; Ruf, O.; Schmidt, C.; Appel, N.; Kleinschrodt, A.; Montenegro, S.; Nüchter, A. In Proceedings IAA-ASS-17 : International Academy of Astronautics, Vol. 163 of Advances in the Astronautical Sciences 4th IAA Dynamics and Control of Space Systems Conference, pp. 1–14. Univelt, Inc., Rome, Italy, 2018.
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  @inproceedings{IAA2017, address = {Rome, Italy}, author = {Schilling, K. and Tzschichholz, T. and Motroniuk, I. and Aumann, A. and Mammadov, I. and Ruf, O. and Schmidt, C. and Appel, N. and Kleinschrodt, A. and Montenegro, S. and N{\"u}chter, A.}, booktitle = {Proceedings IAA-ASS-17 : International Academy of Astronautics}, keywords = {myown}, month = {05}, number = {IAA-AAS-CU-17-08-02}, pages = {1–14}, publisher = {Univelt, Inc.}, series = {Advances in the Astronautical Sciences 4th IAA Dynamics and Control of Space Systems Conference}, title = {TOM: A formation for photogrammetric earth observation by three cubesats}, volume = 163, year = 2018 }
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  Reconstructing the subsurface of planetary volcanic analogues: ERT imaging of Lanzarote lava tubes complemented with drone stereogrammetry, surface and in-cave LiDAR and seismic investigations (Poster). Torrese, P.; Rossi, A. Pio; Unnithan, V.; Borrmann, D.; Lauterbach, H.; Ortenzi, G.; Jährig, T.; Pozzobon, R.; Sauro, F.; Santagata, T.; Nüchter, A.; Sohl, F. In Proceedings of the EGU General Assembly 2018, Pico session: Planetary geobiological analogs for Mars and beyond: Field, lab and simulations, Vol. 20. Vienna, Austria, 2018.
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  @inproceedings{EGU2018, address = {Vienna, Austria}, author = {Torrese, P. and Rossi, A. Pio and Unnithan, V. and Borrmann, D. and Lauterbach, H. and Ortenzi, G. and J{\"a}hrig, T. and Pozzobon, R. and Sauro, F. and Santagata, T. and N{\"u}chter, A. and Sohl, F.}, booktitle = {Proceedings of the EGU General Assembly 2018, Pico session: Planetary geobiological analogs for Mars and beyond: Field, lab and simulations}, keywords = {myown}, month = {04}, number = {EGU2018-14285}, title = {{Reconstructing the subsurface of planetary volcanic analogues: ERT imaging of Lanzarote lava tubes complemented with drone stereogrammetry, surface and in-cave LiDAR and seismic investigations (Poster)}}, volume = 20, year = 2018 }
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  Workshop: Large-Scale 3D Point Cloud Processing for Mixed and Augmented Reality. Borrmann, D.; Nüchter, A.; Wiemann, T. In IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct ’08), p. xxxv. 2018.
  • [ Abstract ]
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  The rapid development of 3D scanning technology combined with state-of-the-art mapping algorithms allows to capture 3D point clouds with high resolution and accuracy. The high amount of data collected with LiDAR, RGB-D cameras or generated through SfM approaches makes the direct use of the recorded data for realistic rendering and simulation problematic. Therefore, these point clouds have to be transformed into representations that fulfill the computational requirements for VR and AR setups. In this tutorial participants will be introduced to state-of-the-art methods in point cloud processing and surface reconstruction with open source software to learn the benefits for AR and VR applications by interleaved presentations, software demonstrations and software trials. The focus lies on 3D point cloud data structures (range images, octrees, k-d trees) and algorithms, and their implementation in C/C++. Surface reconstruction using Marching Cubes and other meshing methods will play another central role. Reference material for subtopics like 3D point cloud registration and SLAM, calibration, filtering, segmentation, meshing, and large scale surface reconstruction will be provided. Participants are invited to bring their Linux, MacOS or Windows laptops to gain hands-on experience on practical problems occuring when working with large scale 3D point clouds in VR and AR applications.

  @inproceedings{ISMAR2018, abstract = {The rapid development of 3D scanning technology combined with state-of-the-art mapping algorithms allows to capture 3D point clouds with high resolution and accuracy. The high amount of data collected with LiDAR, RGB-D cameras or generated through SfM approaches makes the direct use of the recorded data for realistic rendering and simulation problematic. Therefore, these point clouds have to be transformed into representations that fulfill the computational requirements for VR and AR setups. In this tutorial participants will be introduced to state-of-the-art methods in point cloud processing and surface reconstruction with open source software to learn the benefits for AR and VR applications by interleaved presentations, software demonstrations and software trials. The focus lies on 3D point cloud data structures (range images, octrees, k-d trees) and algorithms, and their implementation in C/C++. Surface reconstruction using Marching Cubes and other meshing methods will play another central role. Reference material for subtopics like 3D point cloud registration and SLAM, calibration, filtering, segmentation, meshing, and large scale surface reconstruction will be provided. Participants are invited to bring their Linux, MacOS or Windows laptops to gain hands-on experience on practical problems occuring when working with large scale 3D point clouds in VR and AR applications.}, author = {{Borrmann}, D. and {N{\"u}chter}, A. and {Wiemann}, T.}, booktitle = {IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct '08)}, keywords = {myown}, month = 10, pages = {xxxv}, title = {{Workshop: Large-Scale 3D Point Cloud Processing for Mixed and Augmented Reality}}, year = 2018 }
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  Continuous-Time SLAM --- Improving Google’s Cartographer 3D Mapping. Nüchter, A.; Bleier, M.; Schauer, J.; Janotta, P. In Latest Developments in Reality-Based 3D Surveying and Modelling, F. Remondino, A. Georgopoulos, D. Gonzalez-Aguilera, P. Agrafiotis (eds.), pp. 53–73. MDPI, Basel, Switzerland, 2018.
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  This paper shows how to use the result of Google’s simultaneous localization and mapping (SLAM) solution, called Cartographer, to bootstrap a continuous-time SLAM algorithm that was developed by the authors and presented in previous publications. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google’s results. Algorithms and data from Google are used as input for the continuous-time SLAM software. In preceding work, the continuous-time SLAM was successfully applied to a similar backpack system which delivers consistent 3D point clouds even in the absence of an IMU. Continuous-time SLAM means that the trajectory of a mobile mapping system is treated in a semi-rigid fashion, i.e., the trajectory is deformed to yield a consistent 3D point cloud of the measured environment.

  @incollection{MDPI2018, abstract = {This paper shows how to use the result of Google’s simultaneous localization and mapping (SLAM) solution, called Cartographer, to bootstrap a continuous-time SLAM algorithm that was developed by the authors and presented in previous publications. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google’s results. Algorithms and data from Google are used as input for the continuous-time SLAM software. In preceding work, the continuous-time SLAM was successfully applied to a similar backpack system which delivers consistent 3D point clouds even in the absence of an IMU. Continuous-time SLAM means that the trajectory of a mobile mapping system is treated in a semi-rigid fashion, i.e., the trajectory is deformed to yield a consistent 3D point cloud of the measured environment.}, address = {Basel, Switzerland}, author = {N{\"u}chter, A. and Bleier, M. and Schauer, J. and Janotta, P.}, booktitle = {Latest Developments in Reality-Based 3D Surveying and Modelling}, chapter = {Continuous-Time SLAM — Improving Google’s Cartographer 3D Mapping}, editor = {Remondino, F. and Georgopoulos, A. and Gonzalez-Aguilera, D. and Agrafiotis, P.}, keywords = {myown}, month = {01}, pages = {53–73}, publisher = {MDPI}, title = {Continuous-Time SLAM — Improving Google’s Cartographer 3D Mapping}, year = 2018 }
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  Augmented field Geology and Geophysics for Planetary Analogues (Poster). Rossi, A. Pio; Unnithan, V.; Torrese, P.; Borrmann, D.; Nüchter, A.; Lauterbach, H.; Ortenzi, G.; Jährig, T.; Sohl, F. In Proceedings of the EGU General Assembly 2018, Pico session: Planetary geobiological analogs for Mars and beyond: Field, lab and simulations, Vol. 20. Vienna, Austria, 2018.
  • [ BibTeX ]
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  @inproceedings{EGU2018, address = {Vienna, Austria}, author = {Rossi, A. Pio and Unnithan, V. and Torrese, P. and Borrmann, D. and N{\"u}chter, A. and Lauterbach, H. and Ortenzi, G. and J{\"a}hrig, T. and Sohl, F.}, booktitle = {Proceedings of the EGU General Assembly 2018, Pico session: Planetary geobiological analogs for Mars and beyond: Field, lab and simulations}, keywords = {myown}, month = {04}, number = {EGU2018-6389}, title = {{Augmented field Geology and Geophysics for Planetary Analogues (Poster)}}, volume = 20, year = 2018 }
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  Benchmarking Structure from Motion Algorithms of Urban Environments with Applications to Reconnaissance in Search and Rescue Scenarios. Martell, A.; Lauterbach, H. A.; Schilling, K.; Nüchter, A. In Proceedings of the 16th IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’18), pp. 1–7. Philadelphia, PA, USA, 2018.
  • [ BibTeX ]
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  @inproceedings{8468612, address = {Philadelphia, PA, USA}, author = {Martell, A. and Lauterbach, H. A. and Schilling, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the 16th IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR '18)}, keywords = {author}, month = {08}, pages = {1–7}, title = {{Benchmarking Structure from Motion Algorithms of Urban Environments with Applications to Reconnaissance in Search and Rescue Scenarios}}, year = 2018 }
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  Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data. Pfitzner, C.; May, S.; Nüchter, A. In Sensors, 18(5). 2018.
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  This paper describes the estimation of the body weight of a person in front of an RGB-D camera. A survey of different methods for body weight estimation based on depth sensors is given. First, an estimation of people standing in front of a camera is presented. Second, an approach based on a stream of depth images is used to obtain the body weight of a person walking towards a sensor. The algorithm first extracts features from a point cloud and forwards them to an artificial neural network (ANN) to obtain an estimation of body weight. Besides the algorithm for the estimation, this paper further presents an open-access dataset based on measurements from a trauma room in a hospital as well as data from visitors of a public event. In total, the dataset contains 439 measurements. The article illustrates the efficiency of the approach with experiments with persons lying down in a hospital, standing persons, and walking persons. Applicable scenarios for the presented algorithm are body weight-related dosing of emergency patients.

  @article{SENSORS2018, abstract = {This paper describes the estimation of the body weight of a person in front of an RGB-D camera. A survey of different methods for body weight estimation based on depth sensors is given. First, an estimation of people standing in front of a camera is presented. Second, an approach based on a stream of depth images is used to obtain the body weight of a person walking towards a sensor. The algorithm first extracts features from a point cloud and forwards them to an artificial neural network (ANN) to obtain an estimation of body weight. Besides the algorithm for the estimation, this paper further presents an open-access dataset based on measurements from a trauma room in a hospital as well as data from visitors of a public event. In total, the dataset contains 439 measurements. The article illustrates the efficiency of the approach with experiments with persons lying down in a hospital, standing persons, and walking persons. Applicable scenarios for the presented algorithm are body weight-related dosing of emergency patients.}, author = {Pfitzner, C. and May, S. and N{\"u}chter, A.}, journal = {Sensors}, keywords = {myown}, month = {04}, number = 5, title = {Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data}, volume = 18, year = 2018 }

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  Evaluating continuous-time SLAM using a predefined trajectory provided by a robotic arm. Koch, B.; Leblebici, R.; Martell, A.; Jörissen, S.; Schilling, K.; Nüchter, A. In Proceedings of the ISPRS Geospatial Week 2017, Laserscanning 2017, of ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., IV-2/W4, pp. 17–23. Wuhan, China, 2017.
  • [ Abstract ]
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  Recently published approaches to SLAM algorithms process laser sensor measurements and output a map as a point cloud of the environment. Often the actual precision of the map remains unclear, since SLAMalgorithms apply local improvements to the resulting map. Unfortunately, it is not trivial to compare the performance of SLAMalgorithms objectively, especially without an accurate ground truth. This paper presents a novel benchmarking technique that allows to compare a precise map generated with an accurate ground truth trajectory to a map with a manipulated trajectory which was distorted by different forms of noise. The accurate ground truth is acquired by mounting a laser scanner on an industrial robotic arm. The robotic arm is moved on a predefined path while the position and orientation of the end-effector tool are monitored. During this process the 2D profile measurements of the laser scanner are recorded in six degrees of freedom and afterwards used to generate a precise point cloud of the test environment. For benchmarking, an offline continuous-time SLAM algorithm is subsequently applied to remove the inserted distortions. Finally, it is shown that the manipulated point cloud is reversible to its previous state and is slightly improved compared to the original version, since small errors that came into account by imprecise assumptions, sensor noise and calibration errors are removed as well.

  @inproceedings{LS2017, abstract = {Recently published approaches to SLAM algorithms process laser sensor measurements and output a map as a point cloud of the environment. Often the actual precision of the map remains unclear, since SLAMalgorithms apply local improvements to the resulting map. Unfortunately, it is not trivial to compare the performance of SLAMalgorithms objectively, especially without an accurate ground truth. This paper presents a novel benchmarking technique that allows to compare a precise map generated with an accurate ground truth trajectory to a map with a manipulated trajectory which was distorted by different forms of noise. The accurate ground truth is acquired by mounting a laser scanner on an industrial robotic arm. The robotic arm is moved on a predefined path while the position and orientation of the end-effector tool are monitored. During this process the 2D profile measurements of the laser scanner are recorded in six degrees of freedom and afterwards used to generate a precise point cloud of the test environment. For benchmarking, an offline continuous-time SLAM algorithm is subsequently applied to remove the inserted distortions. Finally, it is shown that the manipulated point cloud is reversible to its previous state and is slightly improved compared to the original version, since small errors that came into account by imprecise assumptions, sensor noise and calibration errors are removed as well.}, address = {Wuhan, China}, author = {Koch, B. and Leblebici, R. and Martell, A. and J{\"o}rissen, S. and Schilling, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the ISPRS Geospatial Week 2017, Laserscanning 2017}, keywords = {myown}, month = {09}, pages = {17–23}, series = {ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., IV-2/W4}, title = {Evaluating continuous-time SLAM using a predefined trajectory provided by a robotic arm}, year = 2017 }
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  Chilean underground mine dataset. Leung, K. Y. K.; Lühr, D.; Houshiar, H.; Inostroza, F.; Borrmann, D.; Adams, M.; Nüchter, A.; del Solar, J. R. In International Journal of Robotics Research (IJRR), 36(1), pp. 16–23. 2017.
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  This article presents a robotic dataset collected from the largest underground copper mine in the world. The sensor measurements from a 3D scanning lidar, a 2D radar, and stereo cameras were recorded from an approximately two kilometer traverse of a production-active tunnel. The equipment used and the data collection process is discussed in detail, along with the format of the data. This dataset is suitable for research in robotic navigation, as well as simultaneous localization and mapping. The download instructions are available at the following website http://dataset.amtc.cl.

  @article{IJRR2017, abstract = {This article presents a robotic dataset collected from the largest underground copper mine in the world. The sensor measurements from a 3D scanning lidar, a 2D radar, and stereo cameras were recorded from an approximately two kilometer traverse of a production-active tunnel. The equipment used and the data collection process is discussed in detail, along with the format of the data. This dataset is suitable for research in robotic navigation, as well as simultaneous localization and mapping. The download instructions are available at the following website http://dataset.amtc.cl.}, author = {Leung, K. Y. K. and L{\"u}hr, D. and Houshiar, H. and Inostroza, F. and Borrmann, D. and Adams, M. and N{\"u}chter, A. and del Solar, J. R.}, journal = {International Journal of Robotics Research (IJRR)}, keywords = {imported}, month = {01}, number = 1, pages = {16–23}, title = {{Chilean underground mine dataset}}, volume = 36, year = 2017 }
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  Effective Distinction Of Transparent And Specular Reflective Objects In Point Clouds Of A Multi-Echo Laser Scanner. Koch, R.; May, S.; Nüchter, A. In Proceedings of the 18th IEEE International Conference on Advanced Robotics (ICAR ’17), pp. 566–571. Hong Kong, China, 2017.
  • [ Abstract ]
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  A favoured sensor for mapping is a 3D laser scanner since it allows a wide scanning range, precise measurements, and is usable indoor and outdoor. Hence, a mapping module delivers detailed and high resolution maps which makes it possible to navigate safely. Difficulties result from transparent and specular reflective objects which cause erroneous and dubious measurements. At such objects, based on the incident angle, measurements result from the object surface, an object behind the transparent surface, or an object mirrored with respect to the reflective surface. This paper describes an enhanced Pre-Filter-Module to distinguish between these cases. Two experiments demonstrate the usability and show that for single scans the identification of mentioned objects in 3D is possible. The first experiment was made in an empty room with a mirror. The second experiment was made in a stairway which contains a glass door. Further, results show that a discrimination between a specular reflective and a transparent object is possible. Especially for transparent objects the detected size is restricted to the incident angle. That is why future work concentrates on implementing a post-filter module. Gained experience shows that collecting the data of multiple scans and postprocess them as soon as the object was bypassed will improve the map.

  @inproceedings{ICAR2017, abstract = {A favoured sensor for mapping is a 3D laser scanner since it allows a wide scanning range, precise measurements, and is usable indoor and outdoor. Hence, a mapping module delivers detailed and high resolution maps which makes it possible to navigate safely. Difficulties result from transparent and specular reflective objects which cause erroneous and dubious measurements. At such objects, based on the incident angle, measurements result from the object surface, an object behind the transparent surface, or an object mirrored with respect to the reflective surface. This paper describes an enhanced Pre-Filter-Module to distinguish between these cases. Two experiments demonstrate the usability and show that for single scans the identification of mentioned objects in 3D is possible. The first experiment was made in an empty room with a mirror. The second experiment was made in a stairway which contains a glass door. Further, results show that a discrimination between a specular reflective and a transparent object is possible. Especially for transparent objects the detected size is restricted to the incident angle. That is why future work concentrates on implementing a post-filter module. Gained experience shows that collecting the data of multiple scans and postprocess them as soon as the object was bypassed will improve the map.}, address = {Hong Kong, China}, author = {Koch, R. and May, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the 18th IEEE International Conference on Advanced Robotics (ICAR '17)}, keywords = {myown}, month = {07}, pages = {566–571}, title = {{Effective Distinction Of Transparent And Specular Reflective Objects In Point Clouds Of A Multi-Echo Laser Scanner}}, year = 2017 }
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  Identification of Transparent and Specular Reflective Material in Laser Scans to Discriminate Affected Measurements for Faultless Robotic SLAM. Koch, R.; May, S.; Murmann, P.; Nüchter, A. In Journal of Robotics and Autonomous Systems (JRAS), 87, pp. 296–312. 2017.
  • [ Abstract ]
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  Mapping with laser scanners is the state-of-the-art method applied in service, industrial, medical, and rescue robotics. Although a lot of research has been done, maps still suffer from interferences caused by transparent and specular reflective objects. Glass, mirrors, shiny or translucent surfaces cause erroneous measurements depending on the incident angle of the laser beam. In past experiments the Mirror Detector Approach was implemented to determine such measurements with a multi-echo laser scanner. Recognition values are based on their differences in recorded measurements in regard to the distance of the echoes. This paper describes the research to distinguish between reflective and transparent objects. The implemented Mirror Detector was specifically modified for recognition of said objects for which four experiments were conducted; one experiment to show the map of the original Mirror Detector; two experiments to investigate intensity characteristics based on angle, distance, and material; and one experiment to show an applied discrimination with the extended version of the Mirror Detector, the Reflection Classifier Approach. To verify the results, a comparison with existing models was performed. This study showed that shiny metals, like aluminium, etc., provide significant characteristics, while mirrors are to be characterized by a mixed model of glass and shiny metal. Transparent objects turned out to be challenging because their appearance in the sensor data strongly depends on the background. Nevertheless, these experiments show that discrimination of transparent and reflective materials based on the reflected intensity is possible and feasible.

  @article{RAS2017, abstract = {Mapping with laser scanners is the state-of-the-art method applied in service, industrial, medical, and rescue robotics. Although a lot of research has been done, maps still suffer from interferences caused by transparent and specular reflective objects. Glass, mirrors, shiny or translucent surfaces cause erroneous measurements depending on the incident angle of the laser beam. In past experiments the Mirror Detector Approach was implemented to determine such measurements with a multi-echo laser scanner. Recognition values are based on their differences in recorded measurements in regard to the distance of the echoes. This paper describes the research to distinguish between reflective and transparent objects. The implemented Mirror Detector was specifically modified for recognition of said objects for which four experiments were conducted; one experiment to show the map of the original Mirror Detector; two experiments to investigate intensity characteristics based on angle, distance, and material; and one experiment to show an applied discrimination with the extended version of the Mirror Detector, the Reflection Classifier Approach. To verify the results, a comparison with existing models was performed. This study showed that shiny metals, like aluminium, etc., provide significant characteristics, while mirrors are to be characterized by a mixed model of glass and shiny metal. Transparent objects turned out to be challenging because their appearance in the sensor data strongly depends on the background. Nevertheless, these experiments show that discrimination of transparent and reflective materials based on the reflected intensity is possible and feasible.}, author = {Koch, R. and May, S. and Murmann, P. and N{\"u}chter, A.}, journal = {Journal of Robotics and Autonomous Systems (JRAS)}, keywords = {myown}, month = {01}, pages = {296–312}, title = {{Identification of Transparent and Specular Reflective Material in Laser Scans to Discriminate Affected Measurements for Faultless Robotic SLAM}}, volume = 87, year = 2017 }
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  Low-cost 3D Laser Scanning in Air or Water Using Self-calibrating Structured Light. Bleier, M.; Nüchter, A. In Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3, pp. 105–112. Nafplio, Greece, 2017.
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  In-situ calibration of structured light scanners in underwater environments is time-consuming and complicated. This paper presents a self-calibrating line laser scanning system, which enables the creation of dense 3D models with a single fixed camera and a freely moving hand-held cross line laser projector. The proposed approach exploits geometric constraints, such as coplanarities, to recover the depth information and is applicable without any prior knowledge of the position and orientation of the laser projector. By employing an off-the-shelf underwater camera and a waterproof housing with high power line lasers an affordable 3D scanning solution can be built. In experiments the performance of the proposed technique is studied and compared with 3D reconstruction using explicit calibration. We demonstrate that the scanning system can be applied to above-the-water as well as underwater scenes.

  @inproceedings{3DARCH2017_2, abstract = {In-situ calibration of structured light scanners in underwater environments is time-consuming and complicated. This paper presents a self-calibrating line laser scanning system, which enables the creation of dense 3D models with a single fixed camera and a freely moving hand-held cross line laser projector. The proposed approach exploits geometric constraints, such as coplanarities, to recover the depth information and is applicable without any prior knowledge of the position and orientation of the laser projector. By employing an off-the-shelf underwater camera and a waterproof housing with high power line lasers an affordable 3D scanning solution can be built. In experiments the performance of the proposed technique is studied and compared with 3D reconstruction using explicit calibration. We demonstrate that the scanning system can be applied to above-the-water as well as underwater scenes.}, address = {Nafplio, Greece}, author = {Bleier, M. and N{\"u}chter, A.}, booktitle = {Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures"}, keywords = {imported}, month = {03}, pages = {105–112}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3}, title = {{Low-cost 3D Laser Scanning in Air or Water Using Self-calibrating Structured Light}}, year = 2017 }
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  Digitizing automotive production lines without interrupting assembly operations through an automatic voxel-based removal of moving objects. Schauer, J.; Nüchter, A. In Proceedings of the 13th IEEE International Conference on Control and Automation (ICCA ’17), pp. 701–706. Ohrid, Macedonia, 2017.
  • [ Abstract ]
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  We present an efficient method to partition a point cloud gathered through kinematic laser scanning into static and dynamic points. The presented algorithm utilizes a voxel grid data structure and uses a ray intersection test to mark voxels as dynamic. The algorithm does not require any ego-motion estimations, computationally expensive object recognition or tracking of moving objects over time. It is easy to implement and can be executed on many cores in parallel. We show the viability of this approach by applying our algorithm to a dataset that we gathered by mounting a FARO Focus3D Laser scanner onto a skid which was then sent along a production line for consumer car chassis in a factory of the Volkswagen corporation. Since factory operators are interested in acquiring digital models of their production lines without suspending factory operations, the resulting point cloud will contain many dynamic objects like humans or other car bodies. We show how our algorithm is able to successfully remove these dynamic objects from the resulting point cloud with minimal errors. Our implementation is published under a free license as part of 3DTK.

  @inproceedings{ICCA2017, abstract = {We present an efficient method to partition a point cloud gathered through kinematic laser scanning into static and dynamic points. The presented algorithm utilizes a voxel grid data structure and uses a ray intersection test to mark voxels as dynamic. The algorithm does not require any ego-motion estimations, computationally expensive object recognition or tracking of moving objects over time. It is easy to implement and can be executed on many cores in parallel. We show the viability of this approach by applying our algorithm to a dataset that we gathered by mounting a FARO Focus3D Laser scanner onto a skid which was then sent along a production line for consumer car chassis in a factory of the Volkswagen corporation. Since factory operators are interested in acquiring digital models of their production lines without suspending factory operations, the resulting point cloud will contain many dynamic objects like humans or other car bodies. We show how our algorithm is able to successfully remove these dynamic objects from the resulting point cloud with minimal errors. Our implementation is published under a free license as part of 3DTK.}, address = {Ohrid, Macedonia}, author = {Schauer, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the 13th IEEE International Conference on Control and Automation (ICCA '17)}, keywords = {myown}, month = {07}, pages = {701–706}, title = {{Digitizing automotive production lines without interrupting assembly operations through an automatic voxel-based removal of moving objects}}, year = 2017 }
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  Detection and Purging of Specular Reflective and Transparent Object Influences in 3D Range Measurements. Koch, R.; May, S.; Nüchter, A. In Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3, pp. 377–384. Nafplio, Greece, 2017.
  • [ Abstract ]
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  3D laser scanners are favoured sensors for mapping in mobile service robotics at indoor and outdoor applications, since they deliver precise measurements at a wide scanning range. The resulting maps are detailed since they have a high resolution. Based on these maps robots navigate through rough terrain, fulfil advanced manipulation, and inspection tasks. In case of specular reflective and transparent objects, e.g., mirrors, windows, shiny metals, the laser measurements get corrupted. Based on the type of object and the incident angle of the incoming laser beam there are three results possible: a measurement point on the object plane, a measurement behind the object plane, and a measurement of a reflected object. It is important to detect such situations to be able to handle these corrupted points. This paper describes why it is difficult to distinguish between specular reflective and transparent surfaces. It presents a 3D- Reflection-Pre-Filter Approach to identify specular reflective and transparent objects in point clouds of a multi-echo laser scanner. Furthermore, it filters point clouds from influences of such objects and extract the object properties for further investigations. Based on an Iterative-Closest-Point-algorithm reflective objects are identified. Object surfaces and points behind surfaces are masked according to their location. Finally, the processed point cloud is forwarded to a mapping module. Furthermore, the object surface corners and the type of the surface is broadcasted. Four experiments demonstrate the usability of the 3D-Reflection-Pre-Filter. The first experiment was made in a empty room containing a mirror, the second experiment was made in a stairway containing a glass door, the third experiment was made in a empty room containing two mirrors, the fourth experiment was made in an office room containing a mirror. This paper demonstrate that for single scans the detection of specular reflective and transparent objects in 3D is possible. It is more reliable in 3D as in 2D. Nevertheless, collect the data of multiple scans and post-filter them as soon as the object was bypassed should pursued. This is why future work concentrates on implementing a post-filter module. Besides, it is the aim to improve the discrimination between specular reflective and transparent objects.

  @inproceedings{3DARCH2017_4, abstract = {3D laser scanners are favoured sensors for mapping in mobile service robotics at indoor and outdoor applications, since they deliver precise measurements at a wide scanning range. The resulting maps are detailed since they have a high resolution. Based on these maps robots navigate through rough terrain, fulfil advanced manipulation, and inspection tasks. In case of specular reflective and transparent objects, e.g., mirrors, windows, shiny metals, the laser measurements get corrupted. Based on the type of object and the incident angle of the incoming laser beam there are three results possible: a measurement point on the object plane, a measurement behind the object plane, and a measurement of a reflected object. It is important to detect such situations to be able to handle these corrupted points. This paper describes why it is difficult to distinguish between specular reflective and transparent surfaces. It presents a 3D- Reflection-Pre-Filter Approach to identify specular reflective and transparent objects in point clouds of a multi-echo laser scanner. Furthermore, it filters point clouds from influences of such objects and extract the object properties for further investigations. Based on an Iterative-Closest-Point-algorithm reflective objects are identified. Object surfaces and points behind surfaces are masked according to their location. Finally, the processed point cloud is forwarded to a mapping module. Furthermore, the object surface corners and the type of the surface is broadcasted. Four experiments demonstrate the usability of the 3D-Reflection-Pre-Filter. The first experiment was made in a empty room containing a mirror, the second experiment was made in a stairway containing a glass door, the third experiment was made in a empty room containing two mirrors, the fourth experiment was made in an office room containing a mirror. This paper demonstrate that for single scans the detection of specular reflective and transparent objects in 3D is possible. It is more reliable in 3D as in 2D. Nevertheless, collect the data of multiple scans and post-filter them as soon as the object was bypassed should pursued. This is why future work concentrates on implementing a post-filter module. Besides, it is the aim to improve the discrimination between specular reflective and transparent objects.}, address = {Nafplio, Greece}, author = {Koch, R. and May, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures"}, keywords = {imported}, month = {03}, pages = {377–384}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3}, title = {{Detection and Purging of Specular Reflective and Transparent Object Influences in 3D Range Measurements}}, year = 2017 }
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  Moving-Object Detection From Consecutive Stereo Pairs Using Slanted Plane Smoothing. Chen, L.; Fan, L.; Xie, G.; Huang, K.; Nüchter, A. In IEEE Transactions on Intelligent Transportation Systems, 18(11), pp. 1–10. 2017.
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  Detecting moving objects is of great importance for autonomous unmanned vehicle systems, and a challenging task especially in complex dynamic environments. This paper proposes a novel approach for the detection of moving objects and the estimation of their motion states using consecutive stereo image pairs on mobile platforms. First, we use a variant of the semi-global matching algorithm to compute initial disparity maps. Second, assisted by the initial disparities, boundaries in the image segmentation produced by simple linear iterative clustering are classified into coplanar, hinge, and occlusion. Moving points are obtained during ego-motion estimation by a modified random sample consensus) algorithm without resorting to time-consuming dense optical flow. Finally, the moving objects are extracted by merging superpixels according to the boundary types and their movements. The proposed method is accelerated on the GPU at 20 frames per second. The data which we use for testing and benchmarking is released, thus completing similar data sets. It includes 812 image pairs and 924 moving objects with ground truth for better algorithms evaluation. Experimental results demonstrate that the proposed method achieves competitive results in terms of moving-object detection and their motion state estimation in challenging urban scenarios.

  @article{ITS2017, abstract = {Detecting moving objects is of great importance for autonomous unmanned vehicle systems, and a challenging task especially in complex dynamic environments. This paper proposes a novel approach for the detection of moving objects and the estimation of their motion states using consecutive stereo image pairs on mobile platforms. First, we use a variant of the semi-global matching algorithm to compute initial disparity maps. Second, assisted by the initial disparities, boundaries in the image segmentation produced by simple linear iterative clustering are classified into coplanar, hinge, and occlusion. Moving points are obtained during ego-motion estimation by a modified random sample consensus) algorithm without resorting to time-consuming dense optical flow. Finally, the moving objects are extracted by merging superpixels according to the boundary types and their movements. The proposed method is accelerated on the GPU at 20 frames per second. The data which we use for testing and benchmarking is released, thus completing similar data sets. It includes 812 image pairs and 924 moving objects with ground truth for better algorithms evaluation. Experimental results demonstrate that the proposed method achieves competitive results in terms of moving-object detection and their motion state estimation in challenging urban scenarios.}, author = {Chen, L. and Fan, L. and Xie, G. and Huang, K. and Nüchter, A.}, journal = {IEEE Transactions on Intelligent Transportation Systems}, keywords = {myown}, month = 11, number = 11, pages = {1–10}, title = {Moving-Object Detection From Consecutive Stereo Pairs Using Slanted Plane Smoothing}, volume = 18, year = 2017 }
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  Out of lab calibration of a rotating 2D scanner for 3D mapping. Koch, R.; Böttcher, L.; Jahrsdörfer, M.; Maier, J.; Trommer, M.; May, S.; Nüchter, A. In Proceedings of the SPIE optical metrology, Videometrics, Range Imaging, and Applications, Vol. 10332, pp. 10332 – 10332 . Munich, Germany, 2017.
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  Mapping is an essential task in mobile robotics. To fulfil advanced navigation and manipulation tasks a 3D representation of the environment is required. Applying stereo cameras or Time-of-flight cameras (TOF cameras) are one way to archive this requirement. Unfortunately, they suffer from drawbacks which makes it difficult to map properly. Therefore, costly 3D laser scanners are applied. An inexpensive way to build a 3D representation is to use a 2D laser scanner and rotate the scan plane around an additional axis. A 3D point cloud acquired with such a custom device consists of multiple 2D line scans. Therefore the scanner pose of each line scan need to be determined as well as parameters resulting from a calibration to generate a 3D point cloud. Using external sensor systems are a common method to determine these calibration parameters. This is costly and difficult when the robot needs to be calibrated outside the lab. Thus, this work presents a calibration method applied on a rotating 2D laser scanner. It uses a hardware setup to identify the required parameters for calibration. This hardware setup is light, small, and easy to transport. Hence, an out of lab calibration is possible. Additional a theoretical model was created to test the algorithm and analyse impact of the scanner accuracy. The hardware components of the 3D scanner system are an HOKUYO UTM-30LX-EW 2D laser scanner, a Dynamixel servo-motor, and a control unit. The calibration system consists of an hemisphere. In the inner of the hemisphere a circular plate is mounted. The algorithm needs to be provided with a dataset of a single rotation from the laser scanner. To achieve a proper calibration result the scanner needs to be located in the middle of the hemisphere. By means of geometric formulas the algorithms determine the individual deviations of the placed laser scanner. In order to minimize errors, the algorithm solves the formulas in an iterative process. First, the calibration algorithm was tested with an ideal hemisphere model created in Matlab. Second, laser scanner was mounted differently, the scanner position and the rotation axis was modified. In doing so, every deviation, was compared with the algorithm results. Several measurement settings were tested repeatedly with the 3D scanner system and the calibration system. The results show that the length accuracy of the laser scanner is most critical. It influences the required size of the hemisphere and the calibration accuracy.

  @inproceedings{SPIE2017, abstract = {Mapping is an essential task in mobile robotics. To fulfil advanced navigation and manipulation tasks a 3D representation of the environment is required. Applying stereo cameras or Time-of-flight cameras (TOF cameras) are one way to archive this requirement. Unfortunately, they suffer from drawbacks which makes it difficult to map properly. Therefore, costly 3D laser scanners are applied. An inexpensive way to build a 3D representation is to use a 2D laser scanner and rotate the scan plane around an additional axis. A 3D point cloud acquired with such a custom device consists of multiple 2D line scans. Therefore the scanner pose of each line scan need to be determined as well as parameters resulting from a calibration to generate a 3D point cloud. Using external sensor systems are a common method to determine these calibration parameters. This is costly and difficult when the robot needs to be calibrated outside the lab. Thus, this work presents a calibration method applied on a rotating 2D laser scanner. It uses a hardware setup to identify the required parameters for calibration. This hardware setup is light, small, and easy to transport. Hence, an out of lab calibration is possible. Additional a theoretical model was created to test the algorithm and analyse impact of the scanner accuracy. The hardware components of the 3D scanner system are an HOKUYO UTM-30LX-EW 2D laser scanner, a Dynamixel servo-motor, and a control unit. The calibration system consists of an hemisphere. In the inner of the hemisphere a circular plate is mounted. The algorithm needs to be provided with a dataset of a single rotation from the laser scanner. To achieve a proper calibration result the scanner needs to be located in the middle of the hemisphere. By means of geometric formulas the algorithms determine the individual deviations of the placed laser scanner. In order to minimize errors, the algorithm solves the formulas in an iterative process. First, the calibration algorithm was tested with an ideal hemisphere model created in Matlab. Second, laser scanner was mounted differently, the scanner position and the rotation axis was modified. In doing so, every deviation, was compared with the algorithm results. Several measurement settings were tested repeatedly with the 3D scanner system and the calibration system. The results show that the length accuracy of the laser scanner is most critical. It influences the required size of the hemisphere and the calibration accuracy.}, address = {Munich, Germany}, author = {Koch, R. and B{\"o}ttcher, L. and Jahrsd{\"o}rfer, M. and Maier, J. and Trommer, M. and May, S. and N{\"u}chter, A.}, journal = {Proceedings of the SPIE optical metrology, Videometrics, Range Imaging, and Applications}, keywords = {imported}, month = {06}, pages = {10332 - 10332 - 8}, title = {{Out of lab calibration of a rotating 2D scanner for 3D mapping}}, volume = 10332, year = 2017 }
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  Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods. Lehtola, V.; Kaartinen, H.; Nüchter, A.; Kaijaluoto, R.; Kukko, A.; Litkey, P.; Honkavaara, E.; Rosnell, T.; Vaaja, M.; Virtanen, J.-P.; et al. In Remote Sensing, p. 796. 2017.
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  Accurate three-dimensional (3D) data from indoor spaces are of high importance for various applications in construction, indoor navigation and real estate management. Mobile scanning techniques are offering an efficient way to produce point clouds, but with a lower accuracy than the traditional terrestrial laser scanning (TLS). In this paper, we first tackle the problem of how the quality of a point cloud should be rigorously evaluated. Previous evaluations typically operate on some point cloud subset, using a manually-given length scale, which would perhaps describe the ranging precision or the properties of the environment. Instead, the metrics that we propose perform the quality evaluation to the full point cloud and over all of the length scales, revealing the method precision along with some possible problems related to the point clouds, such as outliers, over-completeness and misregistration. The proposed methods are used to evaluate the end product point clouds of some of the latest methods. In detail, point clouds are obtained from five commercial indoor mapping systems, Matterport, NavVis, Zebedee, Stencil and Leica Pegasus: Backpack, and three research prototypes, Aalto VILMA, FGI Slammer and the Würzburg backpack. These are compared against survey-grade TLS point clouds captured from three distinct test sites that each have different properties. Based on the presented experimental findings, we discuss the properties of the proposed metrics and the strengths and weaknesses of the above mapping systems and then suggest directions for future research.

  @article{REMSEN2017, abstract = {Accurate three-dimensional (3D) data from indoor spaces are of high importance for various applications in construction, indoor navigation and real estate management. Mobile scanning techniques are offering an efficient way to produce point clouds, but with a lower accuracy than the traditional terrestrial laser scanning (TLS). In this paper, we first tackle the problem of how the quality of a point cloud should be rigorously evaluated. Previous evaluations typically operate on some point cloud subset, using a manually-given length scale, which would perhaps describe the ranging precision or the properties of the environment. Instead, the metrics that we propose perform the quality evaluation to the full point cloud and over all of the length scales, revealing the method precision along with some possible problems related to the point clouds, such as outliers, over-completeness and misregistration. The proposed methods are used to evaluate the end product point clouds of some of the latest methods. In detail, point clouds are obtained from five commercial indoor mapping systems, Matterport, NavVis, Zebedee, Stencil and Leica Pegasus: Backpack, and three research prototypes, Aalto VILMA, FGI Slammer and the Würzburg backpack. These are compared against survey-grade TLS point clouds captured from three distinct test sites that each have different properties. Based on the presented experimental findings, we discuss the properties of the proposed metrics and the strengths and weaknesses of the above mapping systems and then suggest directions for future research.}, author = {Lehtola, V. and Kaartinen, H. and N{\"u}chter, A. and Kaijaluoto, R. and Kukko, A. and Litkey, P. and Honkavaara, E. and Rosnell, T. and Vaaja, M. and Virtanen, J.-P. and et al.}, journal = {Remote Sensing}, keywords = {myown}, month = {08}, pages = 796, title = {{Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods}}, year = 2017 }
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  Improving Google’s Cartographer 3D Mapping by Continuous-Time SLAM. Nüchter, A.; Bleier, M.; Schauer, J.; Janotta, P. In Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3, pp. 543–549. Nafplio, Greece, 2017.
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  This paper shows how to use the result of Google's SLAM solution, called Cartographer, to bootstrap our continuous-time SLAM algorithm. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google’s results. We use the algorithms and data from Google as input for our continuous-time SLAM software. We also successfully applied our software to a similar backpack system which delivers consistent 3D point clouds even in absence of an IMU.

  @inproceedings{3DARCH2017_1, abstract = {This paper shows how to use the result of Google's SLAM solution, called Cartographer, to bootstrap our continuous-time SLAM algorithm. The presented approach optimizes the consistency of the global point cloud, and thus improves on Google’s results. We use the algorithms and data from Google as input for our continuous-time SLAM software. We also successfully applied our software to a similar backpack system which delivers consistent 3D point clouds even in absence of an IMU.}, address = {Nafplio, Greece}, author = {N{\"u}chter, A. and Bleier, M. and Schauer, J. and Janotta, P.}, booktitle = {Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures"}, keywords = {myown}, month = {03}, pages = {543–549}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3}, title = {{Improving Google's Cartographer 3D Mapping by Continuous-Time SLAM}}, year = 2017 }
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  Real-time 3D Mine Modelling in the !VAMOS! Project. Bleier, M.; Dias, A.; Ferreira, A.; Pidgeon, J.; Almeida, J.; Silva, E.; Schilling, K.; Nüchter, A. In Real Time Mining, M. Buxton, J. Benndorf (eds.), pp. 91–102. Technische Universität Bergakademie Freiberg, Institut für Markscheidewesen und Geodäsie, Amsterdam, The Netherlands, 2017.
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  The project Viable Alternative Mine Operating System (\textexclamdown VAMOS!) develops a new safe, clean and low visibility mining technique for excavating raw materials from submerged inland mines. During operations, the perception data of the mining vehicle can only be communicated to the operator via a computer interface. In order to assist remote control and facilitate assessing risks a detailed view of the mining process below the water surface is necessary. This paper presents approaches to real-time 3D reconstruction of the mining environment for immersive data visualisation in a virtual reality environment to provide advanced spatial awareness. From the raw survey data a more consistent 3D model is created using post-processing techniques based on a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function (SDF) based mapping is employed to fuse the measurements from multiple views into a single representation and reduce sensor noise. Results of the proposed techniques are demonstrated on a dataset captured in an sub- merged inland mine.

  @inproceedings{RTM2017, abstract = {The project Viable Alternative Mine Operating System (\textexclamdown VAMOS!) develops a new safe, clean and low visibility mining technique for excavating raw materials from submerged inland mines. During operations, the perception data of the mining vehicle can only be communicated to the operator via a computer interface. In order to assist remote control and facilitate assessing risks a detailed view of the mining process below the water surface is necessary. This paper presents approaches to real-time 3D reconstruction of the mining environment for immersive data visualisation in a virtual reality environment to provide advanced spatial awareness. From the raw survey data a more consistent 3D model is created using post-processing techniques based on a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function (SDF) based mapping is employed to fuse the measurements from multiple views into a single representation and reduce sensor noise. Results of the proposed techniques are demonstrated on a dataset captured in an sub- merged inland mine.}, address = {Amsterdam, The Netherlands}, author = {Bleier, M. and Dias, A. and Ferreira, A. and Pidgeon, J. and Almeida, J. and Silva, E. and Schilling, K. and N{\"u}chter, A.}, booktitle = {Real Time Mining}, editor = {Buxton, M. and Benndorf, J.}, keywords = {myown}, month = 10, pages = {91–102}, publisher = {Technische Universität Bergakademie Freiberg, Institut für Markscheidewesen und Geodäsie}, title = {{Real-time 3D Mine Modelling in the !VAMOS! Project}}, year = 2017 }
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  Autonomous 3D Modelling of Indoor Spaces. Lehtola, V.; Kaartinen, H.; Nüchter, A. In GIM International, 31(10), pp. 20–23. 2017.
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  Mobile scanning can be an equally accurate yet more cost-effective solution than traditional terrestrial laser scanning done with tripods. To succeed, however, mobile scanners not only require a suitable combination of sensors, but also reliable and continuous knowledge about where the scanners are located and the direction in which they are pointing during scanning. There are multiple ways to achieve this, which has led to the development of various scientific and commercial solutions. This article compares several mobile scanning solutions for 3D modelling of indoor spaces and highlights their strengths and weaknesses.

  @article{GIM2017, abstract = {Mobile scanning can be an equally accurate yet more cost-effective solution than traditional terrestrial laser scanning done with tripods. To succeed, however, mobile scanners not only require a suitable combination of sensors, but also reliable and continuous knowledge about where the scanners are located and the direction in which they are pointing during scanning. There are multiple ways to achieve this, which has led to the development of various scientific and commercial solutions. This article compares several mobile scanning solutions for 3D modelling of indoor spaces and highlights their strengths and weaknesses.}, author = {Lehtola, V. and Kaartinen, H. and N{\"u}chter, A.}, journal = {GIM International}, keywords = {myown}, month = 10, number = 10, pages = {20–23}, title = {Autonomous 3D Modelling of Indoor Spaces}, volume = 31, year = 2017 }
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  Signed Distance Function Based Surface Reconstruction of a Submerged Inland Mine Using Continuous-Time SLAM. Bleier, M.; Dias, A.; Ferreira, A.; Pidgeon, J.; Almeida, J. M.; Silva, E.; Schilling, K.; Nüchter, A. In Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC WC ’17). Toulouse, France, 2017.
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  The planning of mining operations in water filled open-pit mines requires detailed bathymetry to create a mine plan and assess the involved risks. This paper presents post- processing techniques for creating an improved 3D model from a survey carried out using an autonomous surface vehicle with a multibeam sonar and a GPS/INS navigation system. Inconsistencies of the created point cloud as a result of calibration errors or GPS signal loss are corrected using a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function based mapping is employed to fuse the measurements from multiple runs into a consistent representation and reduce sensor noise. From the signed distance function model we reconstruct a 3D surface mesh. We use this terrain model to establish a virtual reality scene for immersive data visualization of the mining operations for testing and planing during development. Results of the proposed approach are demonstrated on a dataset captured in an abandoned submerged inland mine.

  @inproceedings{WC2017_1, abstract = {The planning of mining operations in water filled open-pit mines requires detailed bathymetry to create a mine plan and assess the involved risks. This paper presents post- processing techniques for creating an improved 3D model from a survey carried out using an autonomous surface vehicle with a multibeam sonar and a GPS/INS navigation system. Inconsistencies of the created point cloud as a result of calibration errors or GPS signal loss are corrected using a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function based mapping is employed to fuse the measurements from multiple runs into a consistent representation and reduce sensor noise. From the signed distance function model we reconstruct a 3D surface mesh. We use this terrain model to establish a virtual reality scene for immersive data visualization of the mining operations for testing and planing during development. Results of the proposed approach are demonstrated on a dataset captured in an abandoned submerged inland mine.}, address = {Toulouse, France}, author = {Bleier, M. and Dias, A. and Ferreira, A. and Pidgeon, J. and Almeida, J. M. and Silva, E. and Schilling, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC WC '17)}, keywords = {myown}, month = {07}, title = {{Signed Distance Function Based Surface Reconstruction of a Submerged Inland Mine Using Continuous-Time SLAM}}, year = 2017 }
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  Teach-In für die 3D-Scan Akquise mit einem Roboter. Struckmeier, O.; Borrmann, D.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2017, Jade Hochschule, pp. 108–119. 2017.
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  Die 3D-Erfassung einer kompletten Umgebung mittels 3D-Laserscanner stellt abhängig von der zu scannenden Umgebung und dem Scanner einen hohen Zeitaufwand für einen menschlichen Operator dar. Der Scanner muss an die einzelnen Scanpositionen bewegt und dort verortet werden. Mit steigender Qualität der Messung nimmt zudem die Dauer der einzelnen Scanvorgänge zu. In diesem Beitrag wird ein Teach-In Ansatz vorgestellt und evaluiert, der den manuelle n Vorgang verkürzt. Dabei führt ein Roboter die vom Vermesser geplanten und eingespeicherten zeitintensiven Schritte automatisch durch und entlastet somit den Bediener.

  @inproceedings{3DTAGE2017, abstract = {Die 3D-Erfassung einer kompletten Umgebung mittels 3D-Laserscanner stellt abhängig von der zu scannenden Umgebung und dem Scanner einen hohen Zeitaufwand für einen menschlichen Operator dar. Der Scanner muss an die einzelnen Scanpositionen bewegt und dort verortet werden. Mit steigender Qualität der Messung nimmt zudem die Dauer der einzelnen Scanvorgänge zu. In diesem Beitrag wird ein Teach-In Ansatz vorgestellt und evaluiert, der den manuelle n Vorgang verkürzt. Dabei führt ein Roboter die vom Vermesser geplanten und eingespeicherten zeitintensiven Schritte automatisch durch und entlastet somit den Bediener.}, author = {Struckmeier, O. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2017, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {108–119}, title = {{Teach-In f{\"u}r die 3D-Scan Akquise mit einem Roboter}}, year = 2017 }
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  Towards Mobile Mapping of Underground Mines. Nüchter, A.; Elseberg, J.; Janotta, P. In Real Time Mining, M. Buxton, J. Benndorf (eds.), pp. 27–38. Technische Universität Bergakademie Freiberg, Institut für Markscheidewesen und Geodäsie, Amsterdam, The Netherlands, 2017.
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  Mobile laser scanning systems automate the acquisition of 3D point clouds of environments. The mapping systems are commonly mounted on cars or ships. This paper presents a flexible mapping solution mounted on an underground vehicle, that is able to map underground mines in 3D in walking speeds. A clever choice of hard- and software enables the system to generate 3D maps without using GPS (global positioning system) information and without relying on highly expensive IMU (inertial measurement unit) systems.

  @inproceedings{RTM2017slam, abstract = {Mobile laser scanning systems automate the acquisition of 3D point clouds of environments. The mapping systems are commonly mounted on cars or ships. This paper presents a flexible mapping solution mounted on an underground vehicle, that is able to map underground mines in 3D in walking speeds. A clever choice of hard- and software enables the system to generate 3D maps without using GPS (global positioning system) information and without relying on highly expensive IMU (inertial measurement unit) systems.}, address = {Amsterdam, The Netherlands}, author = {N{\"u}chter, A. and Elseberg, J. and Janotta, P.}, booktitle = {Real Time Mining}, editor = {Buxton, M. and Benndorf, J.}, keywords = {myown}, month = 10, pages = {27–38}, publisher = {Technische Universität Bergakademie Freiberg, Institut für Markscheidewesen und Geodäsie}, title = {{Towards Mobile Mapping of Underground Mines}}, year = 2017 }
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  Towards Radiometrical Alignment of 3D Point Clouds. Lauterbach, H. A.; Borrmann, D.; Nüchter, A. In Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures", of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3, pp. 419–424. Nafplio, Greece, 2017.
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  3D laser scanners are typically not able to collect color information. Therefore coloring is often done by projecting photos of an additional camera to the 3D scans. The capturing process is time consuming and therefore prone to changes in the environment. The appearance of the colored point cloud is mainly effected by changes of lighting conditions and corresponding camera settings. In case of panorama images these exposure variations are typically corrected by radiometrical aligning the input images to each other. In this paper we adopt existing methods for panorama optimization in order to correct the coloring of point clouds. Therefore corresponding pixels from overlapping images are selected by using geometrically closest points of the registered 3D scans and their neighboring pixels in the images. The dynamic range of images in raw format allows for correction of large exposure differences. Two experiments demonstrate the abilities of the approach.

  @inproceedings{3DARCH2017_3, abstract = {3D laser scanners are typically not able to collect color information. Therefore coloring is often done by projecting photos of an additional camera to the 3D scans. The capturing process is time consuming and therefore prone to changes in the environment. The appearance of the colored point cloud is mainly effected by changes of lighting conditions and corresponding camera settings. In case of panorama images these exposure variations are typically corrected by radiometrical aligning the input images to each other. In this paper we adopt existing methods for panorama optimization in order to correct the coloring of point clouds. Therefore corresponding pixels from overlapping images are selected by using geometrically closest points of the registered 3D scans and their neighboring pixels in the images. The dynamic range of images in raw format allows for correction of large exposure differences. Two experiments demonstrate the abilities of the approach.}, address = {Nafplio, Greece}, author = {Lauterbach, H. A. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the 7th ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures"}, keywords = {myown}, month = {03}, pages = {419–424}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XLII/W3}, title = {{Towards Radiometrical Alignment of 3D Point Clouds}}, year = 2017 }
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  Evaluation of Features from RGB-D Data for Human Body Weight Estimation. Pfitzner, C.; May, S.; Nüchter, A. In Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC WC ’17). Toulouse, France, 2017.
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  Body weight is a crucial parameter when it comes to drug or radiation dosing. In case of emergency treatment time is short so that physicians estimate the body weight by the visual appearance of a patient. Further, visual body weight estimation might be a feature for person identification. This paper presents the anthropometric feature extraction from RGB-D sensor data, recorded from frontal view. The features are forwarded to an artificial neural network for weight estimation. Experiments with 233 people demonstrate the capability of different features for body weight estimation. To prove robustness against sensor modalities, a structured light sensor is used, as well as a time-of-flight sensor. An additional experiment including temperature features from a thermal camera improves the body weight estimation beyond.

  @inproceedings{WC2017_2, abstract = {Body weight is a crucial parameter when it comes to drug or radiation dosing. In case of emergency treatment time is short so that physicians estimate the body weight by the visual appearance of a patient. Further, visual body weight estimation might be a feature for person identification. This paper presents the anthropometric feature extraction from RGB-D sensor data, recorded from frontal view. The features are forwarded to an artificial neural network for weight estimation. Experiments with 233 people demonstrate the capability of different features for body weight estimation. To prove robustness against sensor modalities, a structured light sensor is used, as well as a time-of-flight sensor. An additional experiment including temperature features from a thermal camera improves the body weight estimation beyond.}, address = {Toulouse, France}, author = {Pfitzner, C. and May, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC WC '17)}, keywords = {imported}, month = {07}, title = {{Evaluation of Features from RGB-D Data for Human Body Weight Estimation}}, year = 2017 }
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  Towards robust self-calibration for handheld 3D line laser scanning. Bleier, M.; Nüchter, A. In Proceedings of LowCost 3D 2017, of ISPRS Int. Archieves Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLII-2/W8, pp. 31–36. Hamburg, Germany, 2017.
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  This paper studies self-calibration of a structured light system, which reconstructs 3D information using video from a static consumer camera and a handheld cross line laser projector. Intersections between the individual laser curves and geometric constraints on the relative position of the laser planes are exploited to achieve dense 3D reconstruction. This is possible without any prior knowledge of the movement of the projector. However, inaccurrately extracted laser lines introduce noise in the detected intersection positions and therefore distort the reconstruction result. Furthermore, when scanning objects with specular reflections, such as glossy painted or metalic surfaces, the reflections are often extracted from the camera image as erroneous laser curves. In this paper we investiagte how robust estimates of the parameters of the laser planes can be obtained despite of noisy detections.

  @inproceedings{LC2017, abstract = {This paper studies self-calibration of a structured light system, which reconstructs 3D information using video from a static consumer camera and a handheld cross line laser projector. Intersections between the individual laser curves and geometric constraints on the relative position of the laser planes are exploited to achieve dense 3D reconstruction. This is possible without any prior knowledge of the movement of the projector. However, inaccurrately extracted laser lines introduce noise in the detected intersection positions and therefore distort the reconstruction result. Furthermore, when scanning objects with specular reflections, such as glossy painted or metalic surfaces, the reflections are often extracted from the camera image as erroneous laser curves. In this paper we investiagte how robust estimates of the parameters of the laser planes can be obtained despite of noisy detections.}, address = {Hamburg, Germany}, author = {Bleier, M. and N{\"u}chter, A.}, booktitle = {Proceedings of LowCost 3D 2017}, keywords = {myown}, month = 11, pages = {31–36}, series = {ISPRS Int. Archieves Photogrammetry and Remote Sensing, Spatial Inf. Sci., XLII-2/W8}, title = {Towards robust self-calibration for handheld 3D line laser scanning}, year = 2017 }

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  Effiziente Speicherung großer Punktwolken -- Datenstrukturen für Algorithmen für mobile und terrestrische Laserscansysteme. Nüchter, A. In Terrestrisches Laserscanning (TLS 2016) Beiträge zum 154. DVW-Seminar am 28. und 29. November in Fulda, pp. 105–120. Fulda, Germany, 2016.
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  @inproceedings{TLS2016, address = {Fulda, Germany}, author = {N{\"u}chter, A.}, booktitle = {Terrestrisches Laserscanning (TLS 2016) Beitr{\"a}ge zum 154. DVW-Seminar am 28. und 29. November in Fulda}, keywords = {imported}, month = 11, pages = {105–120}, title = {{Effiziente Speicherung großer Punktwolken – Datenstrukturen für Algorithmen für mobile und terrestrische Laserscansysteme}}, year = 2016 }
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  Performance comparison between state-of-the-art point-cloud based collision detection approaches on the CPU and GPU. Schauer, J.; Bedkowski, J.; Majek, K.; Nüchter, A. In Proceedings of the 4th IFAC Symposium on Telematics Applications (TA ’16), Vol. 49, pp. 54–59. Porto Alegre, Brazil, 2016.
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  We present two fundamentally different approaches to detect collisions between two point clouds and compare their performance on multiple datasets. A collision between points happens if they are closer to each other than a given threshold radius. One approach utilizes the main CPU with a k-d tree datastructure to efficiently carry out fixed range searches around points in 3D while the other mainly executes on a GPU using a regular grid decomposition technique implemented in the CUDA framework. We will show how massively parallel 3D range searches on a grid based datastructure on a GPU performs similarly well as a tree based approach on the CPU with orders of magnitude less parallelization. We also show how each method scales with varying input sizes and how they perform differently well depending on the spatial structure of the input data.

  @inproceedings{TA2016, abstract = {We present two fundamentally different approaches to detect collisions between two point clouds and compare their performance on multiple datasets. A collision between points happens if they are closer to each other than a given threshold radius. One approach utilizes the main CPU with a k-d tree datastructure to efficiently carry out fixed range searches around points in 3D while the other mainly executes on a GPU using a regular grid decomposition technique implemented in the CUDA framework. We will show how massively parallel 3D range searches on a grid based datastructure on a GPU performs similarly well as a tree based approach on the CPU with orders of magnitude less parallelization. We also show how each method scales with varying input sizes and how they perform differently well depending on the spatial structure of the input data.}, address = {Porto Alegre, Brazil}, author = {Schauer, J. and Bedkowski, J. and Majek, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the 4th IFAC Symposium on Telematics Applications (TA '16)}, keywords = {myown}, month = 11, number = 30, pages = {54–59}, title = {{Performance comparison between state-of-the-art point-cloud based collision detection approaches on the CPU and GPU}}, volume = 49, year = 2016 }
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  Automatische Grundrisserstellung mittels Laserscandaten. Borrmann, D.; Leutert, F.; Maurovic, I.; Seder, M.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2016, Jade Hochschule, pp. 108–119. 2016.
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  In den letzten Jahren haben sich Laserscanner zum Stand der Technik bei der Erstellung von Gebäudemodellen entwickelt. Im Gegensatz zur vergleichsweise kurzen Aufnahmezeit bei der eigentlichen Erfassung der Umgebung mit dem Scanner nimmt die Nachbearbeitung der Daten einen deutlich höheren Zeitanteil ein. Eine manuelle Datenanalyse ist zeitaufwändig und fehleranfällig. Dies erhöht den Bedarf an automatischen Verfahren zur quantitativen Erfassung und Charakterisierung von Umgebungen. In diesem Beitrag präsentieren wir eine automatische Grundrisserstellung basierend auf dem 3D Toolkit (3DTK - http://www.threedtk.de). Nach der autonomen Akquise mit einem mobilen Roboter werden die Daten mittels des iterativen Verfahrens der nächsten Punkte (engl. Iterative Closest Point (ICP)) registriert. Anschließend erfolgt eine automatische Vektorisierung eines 2D-Schnitts der Umgebung basierend auf Verfahren aus der Bildverarbeitung. Der so erzeugte Grundriss dient als Grundlage für eine semantische Karte.

  @inproceedings{3DTAGE2016, abstract = {In den letzten Jahren haben sich Laserscanner zum Stand der Technik bei der Erstellung von Gebäudemodellen entwickelt. Im Gegensatz zur vergleichsweise kurzen Aufnahmezeit bei der eigentlichen Erfassung der Umgebung mit dem Scanner nimmt die Nachbearbeitung der Daten einen deutlich höheren Zeitanteil ein. Eine manuelle Datenanalyse ist zeitaufwändig und fehleranfällig. Dies erhöht den Bedarf an automatischen Verfahren zur quantitativen Erfassung und Charakterisierung von Umgebungen. In diesem Beitrag präsentieren wir eine automatische Grundrisserstellung basierend auf dem 3D Toolkit (3DTK - http://www.threedtk.de). Nach der autonomen Akquise mit einem mobilen Roboter werden die Daten mittels des iterativen Verfahrens der nächsten Punkte (engl. Iterative Closest Point (ICP)) registriert. Anschließend erfolgt eine automatische Vektorisierung eines 2D-Schnitts der Umgebung basierend auf Verfahren aus der Bildverarbeitung. Der so erzeugte Grundriss dient als Grundlage für eine semantische Karte.}, author = {Borrmann, D. and Leutert, F. and Maurovic, I. and Seder, M. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2016, Jade Hochschule}, keywords = {imported}, month = {02}, pages = {108–119}, title = {{Automatische Grundrisserstellung mittels Laserscandaten}}, year = 2016 }
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  Neural Network-based Visual Body Weight Estimation for Drug Dosage Finding. Pfitzner, C.; May, S.; Nüchter, A. In Proceedings of the SPIE 9784, Medical Imaging 2016: Image Processing. San Diego, CA, USA, 2016.
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  Body weight adapted drug dosages are important for emergency treatments. This paper describes an improved body weight estimation approach for emergency patients in a trauma room, based on images from a RGBD sensor and a thermal camera. The improvements are archived by several extensions: The sensor fusion of RGBD and thermal camera eases filtering and segmentation of the patient's body from the background. Robustness and accuracy is gained by an artificial neural network (ANN), which considers features from the sensors as input to calculate the patient's body weight, e.g. the patient's volume, surface and shape parameters. The ANN is trained offline with 30 percent of the patients data. Preliminary experiments with 69 real patients show an accuracy close to 90 percent for a threshold of ten percent relative error in real body estimation. Results are compared to the patient's self estimation, a physician's guess and an anthropometric method: If the patient is knowledgeable it is the best possibility for body weight adapted drug dosages with 97 percent accuracy. The treating physicians and the anthropometric estimation achieve an accuracy of approximately 70 percent. The here presented approach gets an accuracy of nearly 90 percent and would be the best solution if a patient can not provide his own body weight and can not be weighted on a scale. These preliminary results demonstrate a sufficient approach for an upcoming clinical trial with 1,000 patients for body weight estimation.

  @inproceedings{MedIm2016, abstract = {Body weight adapted drug dosages are important for emergency treatments. This paper describes an improved body weight estimation approach for emergency patients in a trauma room, based on images from a RGBD sensor and a thermal camera. The improvements are archived by several extensions: The sensor fusion of RGBD and thermal camera eases filtering and segmentation of the patient's body from the background. Robustness and accuracy is gained by an artificial neural network (ANN), which considers features from the sensors as input to calculate the patient's body weight, e.g. the patient's volume, surface and shape parameters. The ANN is trained offline with 30 percent of the patients data. Preliminary experiments with 69 real patients show an accuracy close to 90 percent for a threshold of ten percent relative error in real body estimation. Results are compared to the patient's self estimation, a physician's guess and an anthropometric method: If the patient is knowledgeable it is the best possibility for body weight adapted drug dosages with 97 percent accuracy. The treating physicians and the anthropometric estimation achieve an accuracy of approximately 70 percent. The here presented approach gets an accuracy of nearly 90 percent and would be the best solution if a patient can not provide his own body weight and can not be weighted on a scale. These preliminary results demonstrate a sufficient approach for an upcoming clinical trial with 1,000 patients for body weight estimation.}, address = {San Diego, CA, USA}, author = {Pfitzner, C. and May, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the SPIE 9784, Medical Imaging 2016: Image Processing}, keywords = {myown}, month = {02}, title = {Neural Network-based Visual Body Weight Estimation for Drug Dosage Finding}, year = 2016 }
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  Multi-Robot Localization and Mapping based on Signed Distance Functions. Koch, P.; May, S.; Schmidpeter, M.; Kühn, M.; Pfitzner, C.; Merkl, C.; Koch, R.; Fees, M.; Martin, J.; Nüchter, A. In Journal of Intelligent and Robotic Systems, 83(3), pp. 409–428. 2016.
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  This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. Novelties of the approach are a joint map built in parallel instead of occasional merging of smaller maps and the limited drift localization which requires no loop closure detection. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data, two actual robots operating in a comparably large area as well as a deployment of these units at the Robocup rescue league.

  @article{JINT2016, abstract = {This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. Novelties of the approach are a joint map built in parallel instead of occasional merging of smaller maps and the limited drift localization which requires no loop closure detection. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data, two actual robots operating in a comparably large area as well as a deployment of these units at the Robocup rescue league.}, author = {Koch, P. and May, S. and Schmidpeter, M. and Kühn, M. and Pfitzner, C. and Merkl, C. and Koch, R. and Fees, M. and Martin, J. and N{\"u}chter, A.}, journal = {Journal of Intelligent and Robotic Systems}, keywords = {imported}, month = {09}, number = 3, pages = {409–428}, title = {{Multi-Robot Localization and Mapping based on Signed Distance Functions}}, volume = 83, year = 2016 }
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  Spatial Projection of Thermal Data for Visual Inspection. Leutert, F.; Borrmann, D.; Schilling, K.; Nüchter, A. In Proceedings of the 14th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV ’16), pp. 1–6. Phuket, Thailand, 2016.
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  Since the advent of thermal imaging, devices with a high optical resolution that use detector arrays to capture the emitted radiance in the thermal infrared range of an entire scene simultaneously have developed as a standard in monitoring energy related. They have had a huge impact on the building industry and in manifacturing, where they are commonly used to monitor proecces that require stable temperature conditions. As beneficial as contactless measurements are, the subsequent localization of points of interest in the environment is often difficult. To overcome this problem we propose a portable system that combines thermal imaging with Augmented Reality (AR). The idea of the approach is to project the gathered temperature information back into the scene to facilitate visual inspection.

  @inproceedings{ICARCV2016, abstract = {Since the advent of thermal imaging, devices with a high optical resolution that use detector arrays to capture the emitted radiance in the thermal infrared range of an entire scene simultaneously have developed as a standard in monitoring energy related. They have had a huge impact on the building industry and in manifacturing, where they are commonly used to monitor proecces that require stable temperature conditions. As beneficial as contactless measurements are, the subsequent localization of points of interest in the environment is often difficult. To overcome this problem we propose a portable system that combines thermal imaging with Augmented Reality (AR). The idea of the approach is to project the gathered temperature information back into the scene to facilitate visual inspection.}, address = {Phuket, Thailand}, author = {Leutert, F. and Borrmann, D. and Schilling, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the 14th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV '16)}, keywords = {imported}, month = 11, pages = {1–6}, title = {{Spatial Projection of Thermal Data for Visual Inspection}}, year = 2016 }
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  LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING. Lehtola, V. V.; Virtanen, J-P.; Rönnholm, P.; Nüchter, A. In Proceedings of the ISPRS Congress 2016, of ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., pp. 81–88. Prague, Czech Republic, 2016.
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  Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore likely to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.

  @inproceedings{ISPRSCongress2016, abstract = {Following the pioneering work introduced in [Lehtola et al., ISPRS J. Photogramm. Remote Sens. 99, 2015, pp. 25–29], we extend the state-of-the-art intrinsic localization solution for a single two-dimensional (2D) laser scanner from one into (quasi) three dimensions (3D). By intrinsic localization, we mean that no external sensors are used to localize the scanner, such as inertial measurement devices (IMU) or global navigation satellite systems (GNSS). Specifically, the proposed method builds on a novel concept of local support-based filtering of outliers, which enables the use of six degrees-of-freedom (DoF) simultaneous localization and mapping (SLAM) for the purpose of enacting appropriate trajectory corrections into the previous one-dimensional solution. Moreover, the local support-based filtering concept is platform independent, and is therefore likely to be widely generalizable. The here presented overall method is yet limited into quasi-3D by its inability to recover trajectories with steep curvature, but in the future, it may be further extended into full 3D.}, address = {Prague, Czech Republic}, author = {Lehtola, V. V. and Virtanen, J-P. and R{\"o}nnholm, P. and N{\"u}chter, A.}, booktitle = {Proceedings of the ISPRS Congress 2016}, keywords = {myown}, month = {07}, number = {III-4}, pages = {81–88}, series = {ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci.}, title = {LOCALIZATION CORRECTIONS FOR MOBILE LASER SCANNER USING LOCAL SUPPORT-BASED OUTLIER FILTERING}, year = 2016 }
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  Range Sensors. Konolige, K.; Nüchter, A. In Handbook of Robotics, second , B. Siciliano, O. Khatib (eds.), pp. 783–810. Springer, 2016.
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  @incollection{Handbook2016, author = {Konolige, K. and N{\"u}chter, A.}, booktitle = {Handbook of Robotics}, edition = {second}, editor = {Siciliano, B. and Khatib, O.}, keywords = {myown}, pages = {783–810}, publisher = {Springer}, title = {Range Sensors}, year = 2016 }
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  Localization of a Mobile Laser Scanner via Dimensional Reduction. Lehtola, V. V.; Virtanen, J.-P.; Vaaja, M. T.; Hyyppä, H.; Nüchter, A. In ISPRS Journal of Photogrammetry and Remote Sensing (JPRS), 121, pp. 48–59. 2016.
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  We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.

  @article{JPRS2016, abstract = {We extend the concept of intrinsic localization from a theoretical one-dimensional (1D) solution onto a 2D manifold that is embedded in a 3D space, and then recover the full six degrees of freedom for a mobile laser scanner with a simultaneous localization and mapping algorithm (SLAM). By intrinsic localization, we mean that no reference coordinate system, such as global navigation satellite system (GNSS), nor inertial measurement unit (IMU) are used. Experiments are conducted with a 2D laser scanner mounted on a rolling prototype platform, VILMA. The concept offers potential in being extendable to other wheeled platforms.}, author = {Lehtola, V. V. and Virtanen, J.-P. and Vaaja, M. T. and Hyypp{\"a}, H. and N{\"u}chter, A.}, journal = {ISPRS Journal of Photogrammetry and Remote Sensing (JPRS)}, keywords = {myown}, month = 11, pages = {48–59}, title = {{Localization of a Mobile Laser Scanner via Dimensional Reduction}}, volume = 121, year = 2016 }

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  CASTLE3D -- A Computer Aided System for Labelling Archaeological Excavations in 3D. Houshiar, H.; Borrmann, D.; Elseberg, J.; Nüchter, A.; Winkler, S.; Näth, F. In Proceedings of the XXV International CIPA Symposium, of ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., II-3/W1, pp. 111–118. Taipei, Taiwan, 2015.
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  Documentation of archaeological excavation sites with conventional methods and tools such as hand drawings, measuring tape and archaeological notes is time consuming. This process is prone to human errors and the quality of the documentation depends on the qualification of the archaeologist on site. Use of modern technology and methods in 3D surveying and 3D robotics facilitate and improve this process. Computer-aided systems and databases improve the documentation quality and increase the speed of data acquisition. 3D laser scanning is the state of the art in modelling archaeological excavation sites, historical sites and even entire cities or landscapes. Modern laser scanners are capable of data acquisition of up to 1 million points per second. This provides a very detailed 3D point cloud of the environment. 3D point clouds and 3D models of an excavation site provide a better representation of the environment for the archaeologist and for documentation. The point cloud can be used both for further studies on the excavation and for the presentation of results. This paper introduces a Computer aided system for labelling archaeological excavations in 3D (CASTLE3D). Consisting of a set of tools for recording and georeferencing the 3D data from an excavation site, CASTLE3D is a novel documentation approach in industrial archaeology. It provides a 2D and 3D visualisation of the data and an easy-to-use interface that enables the archaeologist to select regions of interest and to interact with the data in both representations. The 2D visualisation and a 3D orthogonal view of the data provide cuts of the environment that resemble the traditional hand drawings. The 3D perspective view gives a realistic view of the environment. CASTLE3D is designed as an easy-to-use on-site semantic mapping tool for archaeologists. Each project contains a predefined set of semantic information that can be used to label findings in the data. Multiple regions of interest can be joined under one label. Further information such as color, orientation and archaeological notes are added to the label to improve the documentation. The available 3D information allows for easy measurements in the data. The full 3D information of a region of interest can be segmented from the entire data. By joining this data from different georeferenced views the full 3D shape of findings is stored. All the generated documentation in CASTLE3D is exported to an XML format and serves as input for other systems and databases. Apart from presenting the functionalities of CASTLE3D we evaluate its documentation process in a sample project. For this purpose we export the data to the Adiuvabit database (http://adiuvabit.de) where more information is added for further analysis. The documentation process is compared to traditional documentation methods and it is shown how the automated system helps in accelerating the documentation process and decreases errors to a minimum.

  @inproceedings{CIPA2015, abstract = {Documentation of archaeological excavation sites with conventional methods and tools such as hand drawings, measuring tape and archaeological notes is time consuming. This process is prone to human errors and the quality of the documentation depends on the qualification of the archaeologist on site. Use of modern technology and methods in 3D surveying and 3D robotics facilitate and improve this process. Computer-aided systems and databases improve the documentation quality and increase the speed of data acquisition. 3D laser scanning is the state of the art in modelling archaeological excavation sites, historical sites and even entire cities or landscapes. Modern laser scanners are capable of data acquisition of up to 1 million points per second. This provides a very detailed 3D point cloud of the environment. 3D point clouds and 3D models of an excavation site provide a better representation of the environment for the archaeologist and for documentation. The point cloud can be used both for further studies on the excavation and for the presentation of results. This paper introduces a Computer aided system for labelling archaeological excavations in 3D (CASTLE3D). Consisting of a set of tools for recording and georeferencing the 3D data from an excavation site, CASTLE3D is a novel documentation approach in industrial archaeology. It provides a 2D and 3D visualisation of the data and an easy-to-use interface that enables the archaeologist to select regions of interest and to interact with the data in both representations. The 2D visualisation and a 3D orthogonal view of the data provide cuts of the environment that resemble the traditional hand drawings. The 3D perspective view gives a realistic view of the environment. CASTLE3D is designed as an easy-to-use on-site semantic mapping tool for archaeologists. Each project contains a predefined set of semantic information that can be used to label findings in the data. Multiple regions of interest can be joined under one label. Further information such as color, orientation and archaeological notes are added to the label to improve the documentation. The available 3D information allows for easy measurements in the data. The full 3D information of a region of interest can be segmented from the entire data. By joining this data from different georeferenced views the full 3D shape of findings is stored. All the generated documentation in CASTLE3D is exported to an XML format and serves as input for other systems and databases. Apart from presenting the functionalities of CASTLE3D we evaluate its documentation process in a sample project. For this purpose we export the data to the Adiuvabit database (http://adiuvabit.de) where more information is added for further analysis. The documentation process is compared to traditional documentation methods and it is shown how the automated system helps in accelerating the documentation process and decreases errors to a minimum.}, address = {Taipei, Taiwan}, author = {Houshiar, H. and Borrmann, D. and Elseberg, J. and N{\"u}chter, A. and Winkler, S. and N{\"a}th, F.}, booktitle = {Proceedings of the XXV International CIPA Symposium}, keywords = {myown}, month = {09}, pages = {111–118}, series = {ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., II-3/W1}, title = {{CASTLE3D – A Computer Aided System for Labelling Archaeological Excavations in 3D}}, year = 2015 }
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  Libra3D: Body Weight Estimation for Emergency Patients in Clinical Environment with a 3D Structured Light Sensor. Pfitzner, C.; May, S.; Merkl, C.; Breuer, L.; Köhrmann, M.; Braun, J.; Dirauf, F.; Nüchter, A. In Proceedings of the IEEE International Conference Robotics and Automation (ICRA ’15). Seattle, WA, USA, 2015.
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  his paper describes the application of a weight estimation method for emergency patients in clinical environments. The approach applies established algorithms for point cloud processing and filtering to data from a low-cost, structured light sensor. A patient's volume is estimated on the basis of their visible front surface. The approach is currently being tested in the workflow of the emergency room at the Universitätsklinikum Erlangen, Germany. Preliminary results show the accuracy of the approach in relation to other conservative means of weight measurements, for example, by physicians and anthropometric measurements.

  @inproceedings{ICRA2015, abstract = {his paper describes the application of a weight estimation method for emergency patients in clinical environments. The approach applies established algorithms for point cloud processing and filtering to data from a low-cost, structured light sensor. A patient's volume is estimated on the basis of their visible front surface. The approach is currently being tested in the workflow of the emergency room at the Universitätsklinikum Erlangen, Germany. Preliminary results show the accuracy of the approach in relation to other conservative means of weight measurements, for example, by physicians and anthropometric measurements.}, address = {Seattle, WA, USA}, author = {Pfitzner, C. and May, S. and Merkl, C. and Breuer, L. and K{\"o}hrmann, M. and Braun, J. and Dirauf, F. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference Robotics and Automation (ICRA '15)}, keywords = {imported}, month = {05}, title = {{Libra3D: Body Weight Estimation for Emergency Patients in Clinical Environment with a 3D Structured Light Sensor}}, year = 2015 }
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  A Study of Projections for Key Point Based Registration of Panoramic Terrestrial 3D Laser Scans. Houshiar, H.; Elseberg, J.; Borrmann, D.; Nüchter, A. In Journal of Geo-spatial Information Science, 18(1), pp. 11–31. 2015.
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  This paper surveys state-of-the-art image features and descriptors for the task of 3D scan registration based on panoramic reflectance images. As modern terrestrial laser scanners digitize their environment in a spherical way, the sphere has to be projected to a two-dimensional image. To this end, we evaluate the equirectangular, the cylindrical, the Mercator, the rectilinear, the Pannini, the stereographic, and the z-axis projection. We show that the Mercator and the Pannini projection outperform the other projection methods.

  @article{GSIS2015, abstract = {This paper surveys state-of-the-art image features and descriptors for the task of 3D scan registration based on panoramic reflectance images. As modern terrestrial laser scanners digitize their environment in a spherical way, the sphere has to be projected to a two-dimensional image. To this end, we evaluate the equirectangular, the cylindrical, the Mercator, the rectilinear, the Pannini, the stereographic, and the z-axis projection. We show that the Mercator and the Pannini projection outperform the other projection methods.}, author = {Houshiar, H. and Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, journal = {Journal of Geo-spatial Information Science}, keywords = {myown}, month = {01}, number = 1, pages = {11–31}, title = {{A Study of Projections for Key Point Based Registration of Panoramic Terrestrial 3D Laser Scans}}, volume = 18, year = 2015 }
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  Enhanced frontier-based exploration for indoor environment with multiple robots. Al khawaldah, M.; Nüchter, A. In Advanced Robotics, 28(10), pp. 657–669. 2015.
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  n this paper, the exploration and map-building of unknown environment by a team of mobile robots is intensively investigated. A new exploration technique is proposed to increase the exploration efficiency. In particular, the new technique has two main objectives: firstly, it aims at reducing the exploration time and the traveled distance by reducing the overlap which takes place when a certain area in the environment is explored by more than one robot. To achieve this, a new procedure to assign the next target location for each individual robot is proposed. And secondly, it aims at reducing computations complexity required by target selection and path planning tasks. More importantly, the proposed technique obviates the need for environment segmentation complex procedures which is adopted in some previous important research works. The new technique is intensively tested with different environments. The results showed the effectiveness of the proposed technique.

  @article{AR2015, abstract = {n this paper, the exploration and map-building of unknown environment by a team of mobile robots is intensively investigated. A new exploration technique is proposed to increase the exploration efficiency. In particular, the new technique has two main objectives: firstly, it aims at reducing the exploration time and the traveled distance by reducing the overlap which takes place when a certain area in the environment is explored by more than one robot. To achieve this, a new procedure to assign the next target location for each individual robot is proposed. And secondly, it aims at reducing computations complexity required by target selection and path planning tasks. More importantly, the proposed technique obviates the need for environment segmentation complex procedures which is adopted in some previous important research works. The new technique is intensively tested with different environments. The results showed the effectiveness of the proposed technique.}, author = {Al khawaldah, M. and N{\"u}chter, A.}, journal = {Advanced Robotics}, keywords = {imported}, number = 10, pages = {657–669}, title = {{Enhanced frontier-based exploration for indoor environment with multiple robots}}, volume = 28, year = 2015 }
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  A Backpack-Mounted 3D Mobile Scanning System. Nüchter, A.; Borrmann, D.; Elseberg, J.; Redondo, D. In Allgemeine Vermessungs-Nachrichten (AVN), Special Issue MoLAS 2014, 122(10), pp. 301–307. 2015.
  • [ Abstract ]
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  Mobile laser scanning systems automate the acquisition of 3D point clouds of environments. The mapping systems are commonly mounted on cars or ships. This paper presents a mapping solution mounted on a backpack. A clever choice of hard- and software enables the system to generate 3D maps without using GPS (global positioning system) information and without relying on expensive IMU (inertial measurement unit) systems. Therefore, it enables flexible indoor mapping.

  @article{AVN2015_2, abstract = {Mobile laser scanning systems automate the acquisition of 3D point clouds of environments. The mapping systems are commonly mounted on cars or ships. This paper presents a mapping solution mounted on a backpack. A clever choice of hard- and software enables the system to generate 3D maps without using GPS (global positioning system) information and without relying on expensive IMU (inertial measurement unit) systems. Therefore, it enables flexible indoor mapping.}, author = {N{\"u}chter, A. and Borrmann, D. and Elseberg, J. and Redondo, D.}, journal = {Allgemeine Vermessungs-Nachrichten (AVN), Special Issue MoLAS 2014}, keywords = {imported}, month = 10, number = 10, pages = {301–307}, title = {{A Backpack-Mounted 3D Mobile Scanning System}}, volume = 122, year = 2015 }
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  A Man-Portable, IMU-free Mobile Mapping. Nüchter, A.; Borrmann, D.; Koch, P.; Kühn, M.; May, S. In Proceedings of the ISPRS Geospatial Week 2015, Laserscanning 2015, of ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., II-3/W5, pp. 17–23. La Grande Motte, France, 2015.
  • [ Abstract ]
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  Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM in Freiburg in November 2014. In this paper, we present an IMU-free solution.

  @inproceedings{LS2015, abstract = {Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM in Freiburg in November 2014. In this paper, we present an IMU-free solution.}, address = {La Grande Motte, France}, author = {N{\"u}chter, A. and Borrmann, D. and Koch, P. and K{\"u}hn, M. and May, S.}, booktitle = {Proceedings of the ISPRS Geospatial Week 2015, Laserscanning 2015}, keywords = {myown}, month = {09}, pages = {17–23}, series = {ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., II-3/W5}, title = {A Man-Portable, IMU-free Mobile Mapping}, year = 2015 }
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  Collision detection between point clouds using an efficient $k$-d tree implementation. Schauer, J.; Nüchter, A. In Journal Advanced Engineering Informatics (JAdvEI), 29(3), pp. 440–458. 2015.
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  Context: An important task in civil engineering is the detection of collisions of a 3D model with an environment representation. Existing methods using the structure gauge provide an insufficient measure because the model either rotates or because the trajectory makes tight turns through narrow passages. This is the case in either automotive assembly lines or in narrow train tunnels. Objective: Given two point clouds, one of the environment and one of a model and a trajectory with six degrees of freedom along which the model moves through the environment, find all colliding points of the environment with the model within a certain clearance radius. Method: This paper presents two collision detection (CD) methods called kd-CD and kd-CD-simple and two penetration depth (PD) calculation methods called kd-PD and kd-PD-fast. All four methods are based on searches in a k-d tree representation of the environment. The creation of the k-d tree, its search methods and other features will be explained in the scope of their use to detect collisions and calculate depths of penetration. Results: The algorithms are benchmarked by moving the point cloud of a train wagon with 2.5 million points along the point cloud of a 1144m long train track through a narrow tunnel with overall 18.92 million points. Points where the wagon collides with the tunnel wall are visually highlighted with their penetration depth. With a safety margin of 5cm kd-PD-simple finds all colliding points on its trajectory which is sampled into 19,392 positions in 77s on a standard desktop machine of 1.6GHz. Conclusion: The presented methods for collision detection and penetration depth calculation are shown to solve problems for which the structure gauge is an insufficient measure. The underlying k-d tree is shown to be an effective data structure for the required look-up operations.

  @article{ADVEI2015, abstract = {Context: An important task in civil engineering is the detection of collisions of a 3D model with an environment representation. Existing methods using the structure gauge provide an insufficient measure because the model either rotates or because the trajectory makes tight turns through narrow passages. This is the case in either automotive assembly lines or in narrow train tunnels. Objective: Given two point clouds, one of the environment and one of a model and a trajectory with six degrees of freedom along which the model moves through the environment, find all colliding points of the environment with the model within a certain clearance radius. Method: This paper presents two collision detection (CD) methods called kd-CD and kd-CD-simple and two penetration depth (PD) calculation methods called kd-PD and kd-PD-fast. All four methods are based on searches in a k-d tree representation of the environment. The creation of the k-d tree, its search methods and other features will be explained in the scope of their use to detect collisions and calculate depths of penetration. Results: The algorithms are benchmarked by moving the point cloud of a train wagon with 2.5 million points along the point cloud of a 1144m long train track through a narrow tunnel with overall 18.92 million points. Points where the wagon collides with the tunnel wall are visually highlighted with their penetration depth. With a safety margin of 5cm kd-PD-simple finds all colliding points on its trajectory which is sampled into 19,392 positions in 77s on a standard desktop machine of 1.6GHz. Conclusion: The presented methods for collision detection and penetration depth calculation are shown to solve problems for which the structure gauge is an insufficient measure. The underlying k-d tree is shown to be an effective data structure for the required look-up operations.}, author = {Schauer, J. and N{\"u}chter, A.}, journal = {Journal Advanced Engineering Informatics (JAdvEI)}, keywords = {myown}, month = {08}, number = 3, pages = {440–458}, title = {Collision detection between point clouds using an efficient $k$-d tree implementation}, volume = 29, year = 2015 }
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  Das Castle3D Framework zur fortlaufenden semantischen 3D-Kartierung von archäologischen Ausgrabungsstätten. Borrmann, D.; Houshiar, H.; Elseberg, J.; Nüchter, A; Näth, F.; Winkler, S. In Allgemeine Vermessungs-Nachrichten (AVN), 122(6/7), pp. 233–246. 2015.
  • [ Abstract ]
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  Das 3D Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie vor durch die Entwicklung einer standardisierten Herangehensweise an die computerunterstützte Dokumentation einer archäologischen Ausgrabungsstätten. Ausserdem wird eine Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsstätten vorgestellt, die den Hauptbestandteil der Arbeitskette abdecken. Wir stellen ein effizientes Werkzeug zur Verfügung für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

  @article{AVN2015_1, abstract = {Das 3D Laserscanning ist Stand der Technik bei der Modellierung arch{\"a}ologischer Ausgrabungsst{\"a}tten, historischer Anlagen und sogar ganzer St{\"a}dte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsst{\"a}tte ist eine wesentliche arch{\"a}ologische Aufgabe. Ein automatisiertes System w{\"u}rde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Arch{\"a}ologie vor durch die Entwicklung einer standardisierten Herangehensweise an die computerunterst{\"u}tzte Dokumentation einer arch{\"a}ologischen Ausgrabungsst{\"a}tten. Ausserdem wird eine Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsst{\"a}tten vorgestellt, die den Hauptbestandteil der Arbeitskette abdecken. Wir stellen ein effizientes Werkzeug zur Verf{\"u}gung f{\"u}r die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Arch{\"a}ologen ein einfach zu bedienendes Tool f{\"u}r die semantische Kartierung vor Ort zu bieten. Es enth{\"a}lt Funktionen f{\"u}r die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe f{\"u}r andere Systeme und Datenbanken.}, author = {Borrmann, D. and Houshiar, H. and Elseberg, J. and N{\"u}chter, A and N{\"a}th, F. and Winkler, S.}, journal = {Allgemeine Vermessungs-Nachrichten (AVN)}, keywords = {imported}, number = {6/7}, pages = {233–246}, title = {Das Castle3D Framework zur fortlaufenden semantischen 3D-Kartierung von archäologischen Ausgrabungsstätten}, volume = 122, year = 2015 }
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  Multi-Robot Localization and Mapping based on Signed Distance Functions. Koch, P.; May, S.; Schmidpeter, M.; Kühn, M.; Pfitzner, C.; Merkl, C.; Koch, R.; Fees, M.; Martin, J.; Nüchter, A. In Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC ’15), pp. 77–82. Vila Real, Portugal, 2015.
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  This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data as well as two actual robots operating in a comparably large area.

  @inproceedings{ICARSC2015, abstract = {This publication describes a 2D Simultaneous Localization and Mapping approach applicable to multiple mobile robots. The presented strategy uses data of 2D LIDAR sensors to build a dynamic representation based on Signed Distance Functions. A multi-threaded software architecture performs registration and data integration in parallel allowing for drift-reduced pose estimation of multiple robots. Experiments are provided demonstrating the application with single and multiple robot mapping using simulated data, public accessible recorded data as well as two actual robots operating in a comparably large area.}, address = {Vila Real, Portugal}, author = {Koch, P. and May, S. and Schmidpeter, M. and K{\"u}hn, M. and Pfitzner, C. and Merkl, C. and Koch, R. and Fees, M. and Martin, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC '15)}, keywords = {imported}, month = {04}, pages = {77–82}, title = {{Multi-Robot Localization and Mapping based on Signed Distance Functions}}, year = 2015 }
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  Detection of Specular Reflections in Range Measurements for Faultless Robotic SLAM. Koch, R.; May, S.; Koch, P.; Kühn, M.; Nüchter, A. In Proceedings of ROBOT’2015: Second Iberian Robotics Conference, Advances in Robotics, Volume 1, Vol. 114 of Advances in Intelligent Systems and Computing, pp. 133–145. Springer, Lisbon, Portugal, 2015.
  • [ Abstract ]
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  Laser scanners are state-of-the-art devices used for mapping in service, industry, medical and rescue robotics. Although a lot of work has been done in laser-based SLAM, maps still suffer from interferences caused by objects like glass, mirrors and shiny or translucent surfaces. Depending on the surface's reflectivity, a laser beam is deflected such that returned measurements provide wrong distance data. At certain positions phantom-like objects appear. This paper describes a specular reflectance detection approach applicable to the emerging technology of multi-echo laser scanners in order to identify and filter reflective objects. Two filter stages are implemented. The first filter reduces errors in current scans on the fly. A second filter evaluates a set of laser scans, triggered as soon as a reflective surface has been passed. This makes the reflective surface detection more robust and is used to refine the registered map. Experiments demonstrate the detection and elimination of reflection errors. They show improved localization and mapping in environments containing mirrors and large glass fronts is improved.

  @inproceedings{ROBOT2015, abstract = {Laser scanners are state-of-the-art devices used for mapping in service, industry, medical and rescue robotics. Although a lot of work has been done in laser-based SLAM, maps still suffer from interferences caused by objects like glass, mirrors and shiny or translucent surfaces. Depending on the surface's reflectivity, a laser beam is deflected such that returned measurements provide wrong distance data. At certain positions phantom-like objects appear. This paper describes a specular reflectance detection approach applicable to the emerging technology of multi-echo laser scanners in order to identify and filter reflective objects. Two filter stages are implemented. The first filter reduces errors in current scans on the fly. A second filter evaluates a set of laser scans, triggered as soon as a reflective surface has been passed. This makes the reflective surface detection more robust and is used to refine the registered map. Experiments demonstrate the detection and elimination of reflection errors. They show improved localization and mapping in environments containing mirrors and large glass fronts is improved.}, address = {Lisbon, Portugal}, author = {Koch, R. and May, S. and Koch, P. and K{\"u}hn, M. and N{\"u}chter, A.}, booktitle = {Proceedings of ROBOT'2015: Second Iberian Robotics Conference, Advances in Robotics, Volume 1}, keywords = {imported}, pages = {133–145}, publisher = {Springer}, series = {Advances in Intelligent Systems and Computing}, title = {Detection of Specular Reflections in Range Measurements for Faultless Robotic SLAM}, volume = 114, year = 2015 }
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  Towards Globally Consistent Scan Matching With Ground Truth Integration. Gailis, J.; Nüchter, A. In Proceedings of the ISPRS International Conference on Photogrammetric Image Analysis (PIA ’15), of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-3/W2, pp. 59–64. Munich, Germany, 2015.
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  The scan matching based simultaneous localization and mapping method with six dimensional poses is capable of creating a three dimensional point cloud map of the environment, as well as estimating the six dimensional path that the vehicle has travelled. The essence of it is the registering and matching of sequentially acquired 3D laser scans, while moving along a path, in a common coordinate frame in order to provide 6D pose estimations at the respective positions, as well as create a three dimensional map of the environment. An approach that could drastically improve the reliability of acquired data is to integrate available ground truth information. This paper is about implementing such functionality as a contribution to 6D SLAM (simultaneous localization and mapping with 6 DoF) in the 3DTK – The 3D Toolkit software (Nüchter and Lingemann, 2011), as well as test the functionality of the implementation using real world datasets.

  @inproceedings{PIA2015, abstract = {The scan matching based simultaneous localization and mapping method with six dimensional poses is capable of creating a three dimensional point cloud map of the environment, as well as estimating the six dimensional path that the vehicle has travelled. The essence of it is the registering and matching of sequentially acquired 3D laser scans, while moving along a path, in a common coordinate frame in order to provide 6D pose estimations at the respective positions, as well as create a three dimensional map of the environment. An approach that could drastically improve the reliability of acquired data is to integrate available ground truth information. This paper is about implementing such functionality as a contribution to 6D SLAM (simultaneous localization and mapping with 6 DoF) in the 3DTK – The 3D Toolkit software (Nüchter and Lingemann, 2011), as well as test the functionality of the implementation using real world datasets.}, address = {Munich, Germany}, author = {Gailis, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the ISPRS International Conference on Photogrammetric Image Analysis (PIA '15)}, keywords = {imported}, month = {02}, pages = {59–64}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-3/W2}, title = {{Towards Globally Consistent Scan Matching With Ground Truth Integration}}, year = 2015 }
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  Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency. Demisse, G.; Borrmann, D.; Nüchter, A. In Journal of Intelligent and Robotic Systems, 77(1), pp. 55–72. 2015.
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  In recent years 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited because most models are pure representations with no or little associated semantics. In this paper we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Among other things, these algorithms enable the system to differentiate between objects in a room and objects that are part of the room, e.g. floor, windows. Subsequently, the thermal information is used to construct a stochastic mathematical model– namely Markov Random Field– of the temperature distribution of the detected windows. As a result, the MAP(Maximum a posteriori) framework is used to further label the windows as either open, closed or damaged based upon their temperature distribution. The experimental results showed the robustness of the techniques. Furthermore, a strategy to optimize the free parameters is described, in cases where there is a sample training dataset.

  @article{JINT2015, abstract = {In recent years 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited because most models are pure representations with no or little associated semantics. In this paper we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Among other things, these algorithms enable the system to differentiate between objects in a room and objects that are part of the room, e.g. floor, windows. Subsequently, the thermal information is used to construct a stochastic mathematical model– namely Markov Random Field– of the temperature distribution of the detected windows. As a result, the MAP(Maximum a posteriori) framework is used to further label the windows as either open, closed or damaged based upon their temperature distribution. The experimental results showed the robustness of the techniques. Furthermore, a strategy to optimize the free parameters is described, in cases where there is a sample training dataset.}, author = {Demisse, G. and Borrmann, D. and N{\"u}chter, A.}, journal = {Journal of Intelligent and Robotic Systems}, keywords = {myown}, month = {01}, number = 1, pages = {55–72}, title = {{Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency}}, volume = 77, year = 2015 }
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  Evaluation of Methods for Robotic Mapping of Cultural Heritage Sites. Borrmann, D.; Hess, R.; Eck, D.; Houshiar, H.; Nüchter, A.; Schilling, K. In Proceedings of the 2th IFAC conference on Embedded Systems, Computer Intelligence and Telematics (CESCIT ’15), pp. 105–110. Maribor, Slovenia, 2015.
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  In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in the Würzburg Residence. Methods for automatic 3D color reconstructions of cultural heritage sites are evaluated in this paper.

  @inproceedings{CESCIT2015, abstract = {In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in the Würzburg Residence. Methods for automatic 3D color reconstructions of cultural heritage sites are evaluated in this paper.}, address = {Maribor, Slovenia}, author = {Borrmann, D. and Hess, R. and Eck, D. and Houshiar, H. and N{\"u}chter, A. and Schilling, K.}, booktitle = {Proceedings of the 2th IFAC conference on Embedded Systems, Computer Intelligence and Telematics (CESCIT '15)}, keywords = {myown}, month = {06}, pages = {105–110}, title = {{Evaluation of Methods for Robotic Mapping of Cultural Heritage Sites}}, year = 2015 }
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  Evaluation of a Backpack-Mounted 3D Mobile Scanning System. Lauterbach, H. A.; Borrmann, D.; Hess, R.; Eck, D.; Schilling, K.; Nüchter, A. In Remote Sensing, 7(10), pp. 13753–13781. 2015.
  • [ Abstract ]
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  Recently, several backpack-mounted systems, also known as personal laser scanning systems, have been developed. They consist of laser scanners or cameras that are carried by a human operator to acquire measurements of the environment while walking. These systems were first designed to overcome the challenges of mapping indoor environments with doors and stairs. While the human operator inherently has the ability to open doors and to climb stairs, the flexible movements introduce irregularities of the trajectory to the system. To compete with other mapping systems, the accuracy of these systems has to be evaluated. In this paper, we present an extensive evaluation of our backpack mobile mapping system in indoor environments. It is shown that the system can deal with the normal human walking motion, but has problems with irregular jittering. Moreover, we demonstrate the applicability of the backpack in a suitable urban scenario.

  @article{REMSEN2015, abstract = {Recently, several backpack-mounted systems, also known as personal laser scanning systems, have been developed. They consist of laser scanners or cameras that are carried by a human operator to acquire measurements of the environment while walking. These systems were first designed to overcome the challenges of mapping indoor environments with doors and stairs. While the human operator inherently has the ability to open doors and to climb stairs, the flexible movements introduce irregularities of the trajectory to the system. To compete with other mapping systems, the accuracy of these systems has to be evaluated. In this paper, we present an extensive evaluation of our backpack mobile mapping system in indoor environments. It is shown that the system can deal with the normal human walking motion, but has problems with irregular jittering. Moreover, we demonstrate the applicability of the backpack in a suitable urban scenario.}, author = {Lauterbach, H. A. and Borrmann, D. and Hess, R. and Eck, D. and Schilling, K. and N{\"u}chter, A.}, journal = {Remote Sensing}, keywords = {imported}, number = 10, pages = {13753–13781}, title = {Evaluation of a Backpack-Mounted 3D Mobile Scanning System}, volume = 7, year = 2015 }
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  Intelligent Mobile System for Improving Spatial Design Support and Security Inside Buildings. Bedkowski, J.; Majek, K.; Majek, P.; Musialik, P.; Pelka, M.; Nüchter, A. In Mobile Networks and Applications, 20(6), pp. 1–14. 2015.
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  This paper concerns an intelligent mobile application for spatial design support and security domain. Mobility has two aspects in our research: The first one is the usage of mobile robots for 3D mapping of urban areas and for performing some specific tasks. The second mobility aspect is related with a novel Software as a Ser- vice system that allows access to robotic functionalities and data over the Ethernet, thus we demonstrate the use of the novel NVIDIA GRID technology allowing to virtualize the graphic processing unit. We introduce Complex Shape Histogram, a core component of our artificial intelligence engine, used for classifying 3D point clouds with a Support Vector Machine. We use Complex Shape Histograms also for loop closing detection in the simultaneous localization and mapping algorithm. Our intelligent mobile system is built on top of the Qualitative Spatio-Temporal Representa- tion and Reasoning framework. This framework defines an ontology and a semantic model, which are used for building the intelligent mobile user interfaces. We show experiments demonstrating advantages of our approach. In addition, we test our prototypes in the field after the end-user case studies demonstrating a relevant contribution for future intelligent mobile systems that merge mobile robots with novel data centers.

  @article{MNAA2015, abstract = {This paper concerns an intelligent mobile application for spatial design support and security domain. Mobility has two aspects in our research: The first one is the usage of mobile robots for 3D mapping of urban areas and for performing some specific tasks. The second mobility aspect is related with a novel Software as a Ser- vice system that allows access to robotic functionalities and data over the Ethernet, thus we demonstrate the use of the novel NVIDIA GRID technology allowing to virtualize the graphic processing unit. We introduce Complex Shape Histogram, a core component of our artificial intelligence engine, used for classifying 3D point clouds with a Support Vector Machine. We use Complex Shape Histograms also for loop closing detection in the simultaneous localization and mapping algorithm. Our intelligent mobile system is built on top of the Qualitative Spatio-Temporal Representa- tion and Reasoning framework. This framework defines an ontology and a semantic model, which are used for building the intelligent mobile user interfaces. We show experiments demonstrating advantages of our approach. In addition, we test our prototypes in the field after the end-user case studies demonstrating a relevant contribution for future intelligent mobile systems that merge mobile robots with novel data centers.}, author = {Bedkowski, J. and Majek, K. and Majek, P. and Musialik, P. and Pelka, M. and N{\"u}chter, A.}, journal = {Mobile Networks and Applications}, keywords = {myown}, number = 6, pages = {1–14}, title = {{Intelligent Mobile System for Improving Spatial Design Support and Security Inside Buildings}}, volume = 20, year = 2015 }
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  3D Point Cloud Compression using Conventional Image Compression for Efficient Data Transmission. Houshiar, H.; Nüchter, A. In Proceedings of the XXV International Symposium on Information, Communication and Automation Technologies (ICAT ’15), pp. 1–8. IEEE Xplore, Sarajevo, Bosnia, 2015.
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  Modern 3D laser scanners make it easy to collect large 3D point clouds. In this paper we present the use of conventional image based compression methods for 3D point clouds. We map the point cloud onto panorama images to encode the range, reflectance and color value for each point. An encoding method is presented to map the floating point measured ranges on to a three channel image. The image compression methods are used to compress the generated panorama images. We present the results of several lossless compression methods and the lossy JPEG on point cloud compression. Lossless compression methods are designed to retain the original data. On the other hand lossy compression methods sacrifice the details for higher compression ratio. This produces artefacts in the recovered point cloud data. We study the effects of these artefacts on encoded range data. A filtration process is presented for determination of range outliers from uncompressed point clouds.

  @inproceedings{ICAT2015, abstract = {Modern 3D laser scanners make it easy to collect large 3D point clouds. In this paper we present the use of conventional image based compression methods for 3D point clouds. We map the point cloud onto panorama images to encode the range, reflectance and color value for each point. An encoding method is presented to map the floating point measured ranges on to a three channel image. The image compression methods are used to compress the generated panorama images. We present the results of several lossless compression methods and the lossy JPEG on point cloud compression. Lossless compression methods are designed to retain the original data. On the other hand lossy compression methods sacrifice the details for higher compression ratio. This produces artefacts in the recovered point cloud data. We study the effects of these artefacts on encoded range data. A filtration process is presented for determination of range outliers from uncompressed point clouds.}, address = {Sarajevo, Bosnia}, author = {Houshiar, H. and N{\"u}chter, A.}, booktitle = {Proceedings of the XXV International Symposium on Information, Communication and Automation Technologies (ICAT '15)}, keywords = {imported}, month = 10, pages = {1–8}, publisher = {IEEE Xplore}, title = {{3D Point Cloud Compression using Conventional Image Compression for Efficient Data Transmission}}, year = 2015 }
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  Mirror Identification and Correction of 3D Point Clouds. Käshammer, P.; Nüchter, A. In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures", of IISPRS Archives Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-5/W4, pp. 109–114. Avila, Spain, 2015.
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  In terrestrial laser scanning (TLS), the surface geometry of objects is scanned by laser beams and recorded digitally. This produces a discrete set of scan points, commonly referred to as a point cloud. The coordinates of the scan points are determined by measuring the angles and the time-of-flight relative to the origin (scanner position). However, if it comes to mirror surfaces laser beams are fully reflected, due to the high reflectivity. Mirrors do not appear in the point cloud at all. Instead, for every reflected beam, a incorrect scan point is created behind the actual mirror plane. Consequently, problems arise in multiple derived application fields such as 3D virtual reconstruction of complex architectures. The paper presents a new approach to automatically detect framed rectangular mirrors with known dimensions and to correct the 3D point cloud, using the calculated mirror plane.

  @inproceedings{3DARCH2015_1, abstract = {In terrestrial laser scanning (TLS), the surface geometry of objects is scanned by laser beams and recorded digitally. This produces a discrete set of scan points, commonly referred to as a point cloud. The coordinates of the scan points are determined by measuring the angles and the time-of-flight relative to the origin (scanner position). However, if it comes to mirror surfaces laser beams are fully reflected, due to the high reflectivity. Mirrors do not appear in the point cloud at all. Instead, for every reflected beam, a incorrect scan point is created behind the actual mirror plane. Consequently, problems arise in multiple derived application fields such as 3D virtual reconstruction of complex architectures. The paper presents a new approach to automatically detect framed rectangular mirrors with known dimensions and to correct the 3D point cloud, using the calculated mirror plane.}, address = {Avila, Spain}, author = {K{\"a}shammer, P. and N{\"u}chter, A.}, booktitle = {Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures"}, keywords = {myown}, month = {02}, pages = {109–114}, series = {IISPRS Archives Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-5/W4}, title = {{Mirror Identification and Correction of 3D Point Clouds}}, year = 2015 }
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  Robotic Mapping of Cultural Heritage Sites. Borrmann, D.; Hess, R.; Eck, D.; Nüchter, A.; Schilling, K. In Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures", of ISPRS Archives Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-5/W4, pp. 9–16. Avila, Spain, 2015.
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  In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in two scenarios, Ostia Antica and the Würzburg Residence. The paper describes the steps for creating 3D color reconstructions of these renown cultural heritage sites.

  @inproceedings{3DARCH2015_2, abstract = {In archaeological studies the use of new technologies has moved into focus in the past years creating new challenges such as the processing of the massive amounts of data. In this paper we present steps and processes for smart 3D modelling of environments by use of the mobile robot Irma3D. A robot that is equipped with multiple sensors, most importantly a photo camera and a laser scanner, enables the automation of most of the processes, including data acquisition and registration. The robot was tested in two scenarios, Ostia Antica and the Würzburg Residence. The paper describes the steps for creating 3D color reconstructions of these renown cultural heritage sites.}, address = {Avila, Spain}, author = {Borrmann, D. and Hess, R. and Eck, D. and N{\"u}chter, A. and Schilling, K.}, booktitle = {Proceedings of the 6th ISPRS International Workshop 3D-ARCH 2015: "3D Virtual Reconstruction and Visualization of Complex Architectures"}, keywords = {myown}, month = {02}, pages = {9–16}, series = {ISPRS Archives Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-5/W4}, title = {{Robotic Mapping of Cultural Heritage Sites}}, year = 2015 }

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  Multi-Robot Cooperation for Efficient Exploration. Al khawaldah, M.; Nüchter, A. In AUTOMATIKA -- Journal for Control, Measurement, Electronics, Computing and Communications, 55(3), pp. 276–286. 2014.
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  This paper addresses the problem of exploration of an unknown environment by developing effective exploration strategies for a team of mobile robots equipped with continuously rotating 3D scanners. The main aim of the new strategies is to reduce the exploration time of unknown environment. Unlike most of other published works, to save time, the laser scanners rotate and scan the environment while robots are in motion. Furthermore, the new strategies are able to explore large outdoor environments as a considerable reduction of the required computations, especially those required for path planning, have been achieved. Moreover, another new exploration strategy has been developed so that robots continuously replan the order to visit the remaining unexplored areas according to the new data (i.e. updated map) collected by the robot in question or by the other team members. This new extension led to further enhancements over the above mentioned ones, but with slightly higher computational costs. Finally, to assess our new exploration strategies with different levels of environment complexity, new set of experiments were conducted in environments where obstacles are distributed according to the Hilbert curve. The results of these experiments show the effectiveness of the proposed technique to effectively distribute the robots over the environment. More importantly, we show how the optimal number of robots is related to the environment complexity.

  @article{AUTOMATIKA2014, abstract = {This paper addresses the problem of exploration of an unknown environment by developing effective exploration strategies for a team of mobile robots equipped with continuously rotating 3D scanners. The main aim of the new strategies is to reduce the exploration time of unknown environment. Unlike most of other published works, to save time, the laser scanners rotate and scan the environment while robots are in motion. Furthermore, the new strategies are able to explore large outdoor environments as a considerable reduction of the required computations, especially those required for path planning, have been achieved. Moreover, another new exploration strategy has been developed so that robots continuously replan the order to visit the remaining unexplored areas according to the new data (i.e. updated map) collected by the robot in question or by the other team members. This new extension led to further enhancements over the above mentioned ones, but with slightly higher computational costs. Finally, to assess our new exploration strategies with different levels of environment complexity, new set of experiments were conducted in environments where obstacles are distributed according to the Hilbert curve. The results of these experiments show the effectiveness of the proposed technique to effectively distribute the robots over the environment. More importantly, we show how the optimal number of robots is related to the environment complexity.}, author = {Al khawaldah, M. and N{\"u}chter, A.}, journal = {AUTOMATIKA – Journal for Control, Measurement, Electronics, Computing and Communications}, keywords = {myown}, number = 3, pages = {276–286}, title = {{Multi-Robot Cooperation for Efficient Exploration}}, volume = 55, year = 2014 }
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  Nowy algorytm 6DSLAM wykorzystujacy semantyczne rozpoznanie otoczenia. Bedkowski, J.; Majek, K.; Nüchter, A. In 13 Krajowka Konferencja Robotyki Kudowa Zdroj Prace Naukowe, Elektronika z. 194 Post. Robotyki Tom II, pp. 513–520. 2014.
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  W artykule przedstawiono modyfikację algorytmu 6DSLAM wykorzystującą semantyczne rozpoznawanie otoczenia. Zastosowanie semantycznego podejścia nie tylko poprawia w porównaniu do klasycznej metody dokładność tworzonej mapy metrycznej przez robota mobilnego, ale także umożliwia tworzenie takiej mapy w trudnych warunkach terenowych. Przedstawiono eksperymenty tworzenia mapy metrycznej/semantycznej budynków uwzględniając jazdę poziomą oraz kierunku pionowym po schodach. Porównano wynik z poprzednią implementacją algorytmu 6DSLAM. Nowe podejście poprawia spójność oraz dokładność mapy metrycznej. Zastosowanie semantycznego rozpoznawania otoczenia pozwala na rozszerzenie mapy metrycznej o nowe informacje o charakterze jakościowym, w tym przypadku rozróżniane są ściany, podłoga, sufit oraz punkty charakteryzujące się otoczeniem nieuporządkowanym.

  @inproceedings{ROBOTYKI2014, abstract = {W artykule przedstawiono modyfikację algorytmu 6DSLAM wykorzystującą semantyczne rozpoznawanie otoczenia. Zastosowanie semantycznego podejścia nie tylko poprawia w porównaniu do klasycznej metody dokładność tworzonej mapy metrycznej przez robota mobilnego, ale także umożliwia tworzenie takiej mapy w trudnych warunkach terenowych. Przedstawiono eksperymenty tworzenia mapy metrycznej/semantycznej budynków uwzględniając jazdę poziomą oraz kierunku pionowym po schodach. Porównano wynik z poprzednią implementacją algorytmu 6DSLAM. Nowe podejście poprawia spójność oraz dokładność mapy metrycznej. Zastosowanie semantycznego rozpoznawania otoczenia pozwala na rozszerzenie mapy metrycznej o nowe informacje o charakterze jakościowym, w tym przypadku rozróżniane są ściany, podłoga, sufit oraz punkty charakteryzujące się otoczeniem nieuporządkowanym.}, author = {Bedkowski, J. and Majek, K. and N{\"u}chter, A.}, booktitle = {13 Krajowka Konferencja Robotyki Kudowa Zdroj Prace Naukowe, Elektronika z. 194 Post. Robotyki Tom II}, keywords = {myown}, month = {06}, pages = {513–520}, title = {Nowy algorytm 6DSLAM wykorzystujacy semantyczne rozpoznanie otoczenia}, year = 2014 }
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  Fortlaufende semantische 3D-Kartierung von archäologischen Ausgrabungsstätten. Houshiar, H.; Borrmann, D.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2014, Jade Hochschule, pp. 268–277. 2014.
  • [ Abstract ]
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  Das 3D Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie vor. Er besteht aus einer Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsstätten. Wir stellen ein effizientes Werkzeug zur Verfügung für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.

  @inproceedings{3DTAGE2014, abstract = {Das 3D Laserscanning ist Stand der Technik bei der Modellierung archäologischer Ausgrabungsstätten, historischer Anlagen und sogar ganzer Städte oder Landschaften. Die Dokumentation der Befunde auf einer Ausgrabungsstätte ist eine wesentliche archäologische Aufgabe. Ein automatisiertes System würde diesen Prozess beschleunigen und die Anzahl der Fehler auf ein Minimum reduzieren. Dieser Beitrag stellt einen neuen Ansatz in der Dokumentation industrieller Archäologie vor. Er besteht aus einer Reihe von Tools zur Erfassung und Registrierung von 3D-Daten auf Ausgrabungsstätten. Wir stellen ein effizientes Werkzeug zur Verfügung für die Visualisierung der erworbenen 3D-Punktwolken im 3D- und 2D-Modus. Der Hauptzweck dieser Software ist Archäologen ein einfach zu bedienendes Tool für die semantische Kartierung vor Ort zu bieten. Es enthält Funktionen für die Auswahl und Kennzeichnung von Funden. Jedes Label kann mit weiteren Informationen versehen werden. Diese Daten werden im XML-Format exportiert und dienen als Eingabe für andere Systeme und Datenbanken.}, author = {Houshiar, H. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2014, Jade Hochschule}, keywords = {imported}, month = {02}, pages = {268–277}, title = {{Fortlaufende semantische 3D-Kartierung von arch{\"a}ologischen Ausgrabungsst{\"a}tten}}, year = 2014 }
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  A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios. Li, Qingquan; Chen, Long; Li, Ming; Shaw, Shih-Lung; Nüchter, A. In IEEE Transactions on Vehicular Technology, 63(2), pp. 540–555. 2014.
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  Autonomous vehicle navigation is challenging since various types of road scenarios in real urban environments have to be considered, particularly when only perception sensors are used, without position information. This paper presents a novel real-time optimal-drivable-region and lane detection system for autonomous driving based on the fusion of light detection and ranging (LIDAR) and vision data. Our system uses a multisensory scheme to cover the most drivable areas in front of a vehicle. We propose a feature-level fusion method for the LIDAR and vision data and an optimal selection strategy for detecting the best drivable region. Then, a conditional lane detection algorithm is selectively executed depending on the automatic classification of the optimal drivable region. Our system successfully handles both structured and unstructured roads. The results of several experiments are provided to demonstrate the reliability, effectiveness, and robustness of the system.

  @article{TVT2014, abstract = {Autonomous vehicle navigation is challenging since various types of road scenarios in real urban environments have to be considered, particularly when only perception sensors are used, without position information. This paper presents a novel real-time optimal-drivable-region and lane detection system for autonomous driving based on the fusion of light detection and ranging (LIDAR) and vision data. Our system uses a multisensory scheme to cover the most drivable areas in front of a vehicle. We propose a feature-level fusion method for the LIDAR and vision data and an optimal selection strategy for detecting the best drivable region. Then, a conditional lane detection algorithm is selectively executed depending on the automatic classification of the optimal drivable region. Our system successfully handles both structured and unstructured roads. The results of several experiments are provided to demonstrate the reliability, effectiveness, and robustness of the system.}, author = {Li, Qingquan and Chen, Long and Li, Ming and Shaw, Shih-Lung and N{\"u}chter, A.}, journal = {IEEE Transactions on Vehicular Technology}, keywords = {imported}, month = {02}, number = 2, pages = {540–555}, title = {{A Sensor-Fusion Drivable-Region and Lane-Detection System for Autonomous Vehicle Navigation in Challenging Road Scenarios}}, volume = 63, year = 2014 }
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  A mobile robot based system for fully automated thermal 3D mapping. Borrmann, D.; Nüchter, A.; \DJ{}akulovi\’c}}, M.; Maurovi\’c}}, I.; Petrovi\’c}}, I.; Osmankovi\’c}}, D.; Velagi\’c}}, J. In Journal Advanced Engineering Informatics (JAdvEI), 28(4), pp. 425–440. 2014.
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  It is hard to imagine living in a building without electricity and a heating or cooling system these days. Factories and data centers are equally dependent on a continuous functioning of these systems. As beneficial as this development is for our daily life, the consequences of a failure are critical. Malfunctioning power supplies or temperature regulation systems can cause the close-down of an entire factory or data center. Heat and air conditioning losses in buildings lead to a large waste of the limited energy resources and pollute the environment unnecessarily. To detect these flaws as quickly as possible and to prevent the negative consequences constant monitoring of power lines and heat sources is necessary. To this end, we propose a fully automatic system that creates 3D thermal models of indoor environments. The proposed system consists of a mobile platform that is equipped with a 3D laser scanner, an RGB camera and a thermal camera. A novel 3D exploration algorithm ensures efficient data collection that covers the entire scene. The data from all sensors collected at different positions is joined into one common reference frame using calibration and scan matching. In the post-processing step a model is built and points of interest are automatically detected. A viewer is presented that aids experts in analyzing the heat flow and localizing and identifying heat leaks. Results are shown that demonstrate the functionality of the system.

  @article{ADVEI2014, abstract = {It is hard to imagine living in a building without electricity and a heating or cooling system these days. Factories and data centers are equally dependent on a continuous functioning of these systems. As beneficial as this development is for our daily life, the consequences of a failure are critical. Malfunctioning power supplies or temperature regulation systems can cause the close-down of an entire factory or data center. Heat and air conditioning losses in buildings lead to a large waste of the limited energy resources and pollute the environment unnecessarily. To detect these flaws as quickly as possible and to prevent the negative consequences constant monitoring of power lines and heat sources is necessary. To this end, we propose a fully automatic system that creates 3D thermal models of indoor environments. The proposed system consists of a mobile platform that is equipped with a 3D laser scanner, an RGB camera and a thermal camera. A novel 3D exploration algorithm ensures efficient data collection that covers the entire scene. The data from all sensors collected at different positions is joined into one common reference frame using calibration and scan matching. In the post-processing step a model is built and points of interest are automatically detected. A viewer is presented that aids experts in analyzing the heat flow and localizing and identifying heat leaks. Results are shown that demonstrate the functionality of the system.}, author = {Borrmann, D. and N{\"u}chter, A. and \DJ{}akulovi\'{c}, M. and Maurovi\'{c}, I. and Petrovi\'{c}, I. and Osmankovi\'{c}, D. and Velagi\'{c}, J.}, journal = {Journal Advanced Engineering Informatics (JAdvEI)}, keywords = {myown}, month = 10, number = 4, pages = {425–440}, title = {A mobile robot based system for fully automated thermal 3D mapping}, volume = 28, year = 2014 }
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  Efficient Point Cloud Collision Detection and Analysis in a Tunnel Environment using Kinematic Laser Scanning and k-d Tree Search. Schauer, J.; Nüchter, A. In Proceedings of the Photogrammetric Computer Vision (PCV ’14), of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-3, pp. 289–295. Zürich, Switzerland, 2014.
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  Measuring the structure gauge of tunnels and other narrow passages has so far been the only way to evaluate whether large vehicles can pass through them. But especially for very long vehicles like train wagons and their cargo, the structure gauge is an insufficient measure because the center part of the vehicle between two bogies will inevitably leave the swept volume of its cross section when moving along any other trajectory than a straight line perpendicular to its cross section. In addition, the vehicle as well as the cargo must keep a minimum safety margin from the environment at all points of its trajectory. This paper explores an automated method to check for possible collisions of a model represented by a 3D point cloud moving through the 3D point cloud of an environment. We were given environment data of a train track through a narrow tunnel where simply relying on the structure gauge would indicate that a given wagon would pass through without any collision even though in reality, the train wagon would collide with the inner tunnel wall inside a sharp turn of the tracks. The k-d tree based collision detection method presented in this paper is able to correctly highlight these collisions and indicate the penetration depth of each colliding point of the environment into the model of the train wagon. It can be generalized for any setup where two static point clouds have to be tested for intersection along a trajectory.

  @inproceedings{PCV2014, abstract = {Measuring the structure gauge of tunnels and other narrow passages has so far been the only way to evaluate whether large vehicles can pass through them. But especially for very long vehicles like train wagons and their cargo, the structure gauge is an insufficient measure because the center part of the vehicle between two bogies will inevitably leave the swept volume of its cross section when moving along any other trajectory than a straight line perpendicular to its cross section. In addition, the vehicle as well as the cargo must keep a minimum safety margin from the environment at all points of its trajectory. This paper explores an automated method to check for possible collisions of a model represented by a 3D point cloud moving through the 3D point cloud of an environment. We were given environment data of a train track through a narrow tunnel where simply relying on the structure gauge would indicate that a given wagon would pass through without any collision even though in reality, the train wagon would collide with the inner tunnel wall inside a sharp turn of the tracks. The k-d tree based collision detection method presented in this paper is able to correctly highlight these collisions and indicate the penetration depth of each colliding point of the environment into the model of the train wagon. It can be generalized for any setup where two static point clouds have to be tested for intersection along a trajectory.}, address = {Z{\"u}rich, Switzerland}, author = {Schauer, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the Photogrammetric Computer Vision (PCV '14)}, keywords = {imported}, month = {09}, pages = {289–295}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-3}, title = {{Efficient Point Cloud Collision Detection and Analysis in a Tunnel Environment using Kinematic Laser Scanning and k-d Tree Search}}, year = 2014 }
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  Editorial: Semantic Perception, Mapping and Exploration. Nüchter, A.; Rusu, R. B.; Holz, D.; Munoz, D. In Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Perception, Mapping and Exploration, 62(5), pp. 1–2. 2014.
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  @article{JRAS2014, author = {N{\"u}chter, A. and Rusu, R. B. and Holz, D. and Munoz, D.}, journal = {Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Perception, Mapping and Exploration}, keywords = {imported}, month = {05}, number = 5, pages = {1–2}, title = {{Editorial: Semantic Perception, Mapping and Exploration}}, volume = 62, year = 2014 }
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  Immersive Point Cloud Virtual Environments (Poster). Bruder, G.; Steinicke, F.; Nüchter, A. In Proceedings of IEEE Symposium on 3D User Interfaces 3DUI Proceedings of IEEE Symposium on 3D User Interfaces (3DUI ’14), pp. 161–162. 2014.
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  Today's three-dimensional (3D) virtual environments (VEs) are usually based on textured polygonal 3D models, which represent the appearance and geometry of the virtual world. However, some application domains require other graphical paradigms, which are currently not adequately addressed by 3D user interfaces. We introduce a novel approach for a technical human-robot telepresence setup that allows a human observer to explore a VE, which is a 3D reconstruction of the real world based on point clouds. Such point cloud virtual environments (PCVEs) represent the external environment, and are usually acquired by 3D scanners. We present an application scenario, in which a mobile robot captures 3D scans of a terrestrial environment, which are automatically registered to a coherent PCVE. This virtual 3D reconstruction is displayed in an immersive virtual environment (IVE) in which a user can explore the PCVE. We explain and describe the technical setup, which opens up new vistas of presenting a VE as points rather than a polygonal representation.

  @inproceedings{3DUI2014, abstract = {Today's three-dimensional (3D) virtual environments (VEs) are usually based on textured polygonal 3D models, which represent the appearance and geometry of the virtual world. However, some application domains require other graphical paradigms, which are currently not adequately addressed by 3D user interfaces. We introduce a novel approach for a technical human-robot telepresence setup that allows a human observer to explore a VE, which is a 3D reconstruction of the real world based on point clouds. Such point cloud virtual environments (PCVEs) represent the external environment, and are usually acquired by 3D scanners. We present an application scenario, in which a mobile robot captures 3D scans of a terrestrial environment, which are automatically registered to a coherent PCVE. This virtual 3D reconstruction is displayed in an immersive virtual environment (IVE) in which a user can explore the PCVE. We explain and describe the technical setup, which opens up new vistas of presenting a VE as points rather than a polygonal representation.}, author = {Bruder, G. and Steinicke, F. and Nüchter, A.}, booktitle = {Proceedings of IEEE Symposium on 3D User Interfaces 3DUI Proceedings of IEEE Symposium on 3D User Interfaces (3DUI '14)}, keywords = {myown}, month = {03}, pages = {161–162}, title = {Immersive Point Cloud Virtual Environments (Poster)}, year = 2014 }
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  A Gereralized 2D and 3D Multi-Sensor Data Integration Approach based on Signed Distance Functions for Multi-Modal Robotic Mapping. May, S.; Koch, P.; Koch, R.; Merkl, C.; Pfitzer, C.; A.Nüchter. In Proceedings of th 19th International Workshop on Vision, Modeling and Visualization (VMV ’14). Darmstadt, Germany, 2014.
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  This paper describes a data integration approach for arbitrary 2D/3D depth sensing units exploiting assets of the signed distance function. The underlying framework generalizes the KinectFusion approach with an objectoriented model respecting different sensor modalities. For instance, measurements of 2D/3D laser range finders and RGB-D cameras can be integrated into the same representation. Exemplary, an environment is reconstructed with a 3D laser range finder, while adding fine details from objects of interest by closer inspection with an RGB-D sensor. A typical application of this approach is the exploration in rescue environments, where large-scale mapping is performed on the basis of long-range laser range finders while hollows are inspected with lightweight sensors attached to a manipulator arm.

  @inproceedings{VMV2014, abstract = {This paper describes a data integration approach for arbitrary 2D/3D depth sensing units exploiting assets of the signed distance function. The underlying framework generalizes the KinectFusion approach with an objectoriented model respecting different sensor modalities. For instance, measurements of 2D/3D laser range finders and RGB-D cameras can be integrated into the same representation. Exemplary, an environment is reconstructed with a 3D laser range finder, while adding fine details from objects of interest by closer inspection with an RGB-D sensor. A typical application of this approach is the exploration in rescue environments, where large-scale mapping is performed on the basis of long-range laser range finders while hollows are inspected with lightweight sensors attached to a manipulator arm.}, address = {Darmstadt, Germany}, author = {May, S. and Koch, P. and Koch, R. and Merkl, C. and Pfitzer, C. and A.N{\"u}chter}, booktitle = {Proceedings of th 19th International Workshop on Vision, Modeling and Visualization (VMV '14)}, keywords = {imported}, month = 10, title = {A Gereralized 2D and 3D Multi-Sensor Data Integration Approach based on Signed Distance Functions for Multi-Modal Robotic Mapping}, year = 2014 }
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  Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Perception, Mapping and Exploration. Nüchter, A.; Rusu, R. B.; Holz, D.; Munoz, D. Vol. 62, pp. 617–618. 2014.
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  @periodical{JRAD2014Ed, editor = {N{\"u}chter, A. and Rusu, R. B. and Holz, D. and Munoz, D.}, keywords = {myown}, month = {05}, number = 5, pages = {617–618}, title = {Journal of Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Perception, Mapping and Exploration}, volume = 62, year = 2014 }
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  A sensor skid for precise 3D modeling of production lines. Elseberg, J.; Borrmann, D.; Schauer, J.; Nüchter, A.; Koriath, D.; Rautenberg, U. In Proceedings of the Commision V Symposium Close-range imaging, ranging and applications, of ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., II-5., pp. 117–122. Riva del Garda, Italy, 2014.
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  Motivated by the increasing need of rapid characterization of environments in 3D, we designed and built a sensor skid that automates the work of an operator of terrestrial laser scanners. The system combines terrestrial laser scanning with kinematic laser scanning and uses a novel semi-rigid SLAMmethod. It enables us to digitize factory environments without the need to stop production. The acquired 3D point clouds are precise and suitable to detect objects that collide with items moved along the production line.

  @inproceedings{COMMV2014, abstract = {Motivated by the increasing need of rapid characterization of environments in 3D, we designed and built a sensor skid that automates the work of an operator of terrestrial laser scanners. The system combines terrestrial laser scanning with kinematic laser scanning and uses a novel semi-rigid SLAMmethod. It enables us to digitize factory environments without the need to stop production. The acquired 3D point clouds are precise and suitable to detect objects that collide with items moved along the production line.}, address = {Riva del Garda, Italy}, author = {Elseberg, J. and Borrmann, D. and Schauer, J. and N{\"u}chter, A. and Koriath, D. and Rautenberg, U.}, booktitle = {Proceedings of the Commision V Symposium Close-range imaging, ranging and applications}, keywords = {imported}, month = {06}, pages = {117–122}, series = {ISPRS Annals Photogrammetry and Remote Sensing, Spatial Inf. Sci., II-5.}, title = {{A sensor skid for precise 3D modeling of production lines}}, year = 2014 }

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  Challenges in Using Semantic Knowledge for 3D Object Classification. Gurau, C.; Nüchter, A. In Proceedings of the KI 2013 Workshop on Visual and Spatial Cognition, KIK - KI \& Kognition Workshop Series. Koblenz, Germany, 2013.
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  To cope with a wide variety of tasks, robotic systems need to perceive and understand their environments. In particular, they need a representation of individual objects, as well as contextual relations between them. Visual information is the primary data source used to make predictions and inferences about the world. There exists, however, a growing tendency to introduce high-level semantic knowledge to enable robots to reason about objects. We use the Semantic Web framework to represent knowledge and make inferences about sensor data, in order to detect and classify objects in the environment. The contribution of this work is the identification of several challenges that co-occur when combining sensor data processing with such a reasoning method.

  @inproceedings{KI2013, abstract = {To cope with a wide variety of tasks, robotic systems need to perceive and understand their environments. In particular, they need a representation of individual objects, as well as contextual relations between them. Visual information is the primary data source used to make predictions and inferences about the world. There exists, however, a growing tendency to introduce high-level semantic knowledge to enable robots to reason about objects. We use the Semantic Web framework to represent knowledge and make inferences about sensor data, in order to detect and classify objects in the environment. The contribution of this work is the identification of several challenges that co-occur when combining sensor data processing with such a reasoning method.}, address = {Koblenz, Germany}, author = {Gurau, C. and N{\"u}chter, A.}, booktitle = {Proceedings of the KI 2013 Workshop on Visual and Spatial Cognition, KIK - KI \& Kognition Workshop Series}, keywords = {myown}, month = {09}, title = {{Challenges in Using Semantic Knowledge for 3D Object Classification}}, year = 2013 }
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  Vom Kombinieren von 3D-Modellen mit Farb- und Temperaturinformationen. Borrmann, D.; Houshiar, H.; Elseberg, J.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2013, Jade Hochschule, pp. 246–253. 2013.
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  In den letzten Jahren wurden grosse Fortschritte bei der automatischen Registrierung unterschiedlicher Daten gemacht, zum Beispiel bei Laserscandaten, Fotos und Thermalbilder. So wurden zuverlässige Methoden entwickelt, um Daten aus einem einzelnen Aufnahmeprozess zu registrieren. Probleme bereiten jedoch Daten, die zu unterschiedlichen Zeiten aufgenommen wurden. Dies ist aber essentiell um wertvolle Informationen verschiedener Sensoren zu kombinieren und den Anforderungen an die einzelnen Sensoren gerecht zu werden. Verwertbare Informationen von Thermalbildern erhält man ausschliesslich ohne störende Einflüsse des Sonnenlichts. Farbfotos hingegen werden optimal bei guten Farbverhältnissen aufgenommen. Laserscanner sind relativ robust gegenüber wechselnden Lichtverhältnissen. Für alle Sensoren ist ein Aufnahmezeitpunkt wünschenswert, zu dem möglichst wenige dynamische Objekte die Szene beeinflussen. Üblicherweise ist eine genaue Georeferenzierung der Daten notwendig um Konsistenz zwischen den einzelnen Modellen zu erreichen. Dies erhöht den Aufwand für die Datenakquise erheblich. In diesem Beitrag präsentieren wir robuste Verfahren zur vereinfachten Kombination unterschiedlicher Datensätze.

  @inproceedings{3DTAGE2013_1, abstract = {In den letzten Jahren wurden grosse Fortschritte bei der automatischen Registrierung unterschiedlicher Daten gemacht, zum Beispiel bei Laserscandaten, Fotos und Thermalbilder. So wurden zuverl{\"a}ssige Methoden entwickelt, um Daten aus einem einzelnen Aufnahmeprozess zu registrieren. Probleme bereiten jedoch Daten, die zu unterschiedlichen Zeiten aufgenommen wurden. Dies ist aber essentiell um wertvolle Informationen verschiedener Sensoren zu kombinieren und den Anforderungen an die einzelnen Sensoren gerecht zu werden. Verwertbare Informationen von Thermalbildern erh{\"a}lt man ausschliesslich ohne st{\"o}rende Einfl{\"u}sse des Sonnenlichts. Farbfotos hingegen werden optimal bei guten Farbverh{\"a}ltnissen aufgenommen. Laserscanner sind relativ robust gegen{\"u}ber wechselnden Lichtverh{\"a}ltnissen. F{\"u}r alle Sensoren ist ein Aufnahmezeitpunkt w{\"u}nschenswert, zu dem m{\"o}glichst wenige dynamische Objekte die Szene beeinflussen. {\"U}blicherweise ist eine genaue Georeferenzierung der Daten notwendig um Konsistenz zwischen den einzelnen Modellen zu erreichen. Dies erh{\"o}ht den Aufwand f{\"u}r die Datenakquise erheblich. In diesem Beitrag pr{\"a}sentieren wir robuste Verfahren zur vereinfachten Kombination unterschiedlicher Datens{\"a}tze.}, author = {Borrmann, D. and Houshiar, H. and Elseberg, J. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2013, Jade Hochschule}, keywords = {myown}, month = {02}, pages = {246–253}, title = {{Vom Kombinieren von 3D-Modellen mit Farb- und Temperaturinformationen}}, year = 2013 }
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  Algorithmic solutions for computing accurate maximum likelihood 3D point clouds from mobile laser scanning platforms. Elseberg, J.; Borrmann, D.; Nüchter, A. In Remote Sensing, 5(11), pp. 5871–5906. 2013.
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  Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. We present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors, including odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm, the temporary failure of accurate external positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of the two newly proposed algorithms on a wide variety of datasets.

  @article{REMSEN2013, abstract = {Mobile laser scanning puts high requirements on the accuracy of the positioning systems and the calibration of the measurement system. We present a novel algorithmic approach for calibration with the goal of improving the measurement accuracy of mobile laser scanners. We describe a general framework for calibrating mobile sensor platforms that estimates all configuration parameters for any arrangement of positioning sensors, including odometry. In addition, we present a novel semi-rigid Simultaneous Localization and Mapping (SLAM) algorithm that corrects the vehicle position at every point in time along its trajectory, while simultaneously improving the quality and precision of the entire acquired point cloud. Using this algorithm, the temporary failure of accurate external positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of the two newly proposed algorithms on a wide variety of datasets.}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, journal = {Remote Sensing}, keywords = {imported}, month = 11, number = 11, pages = {5871–5906}, title = {{Algorithmic solutions for computing accurate maximum likelihood 3D point clouds from mobile laser scanning platforms}}, volume = 5, year = 2013 }
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  Automation in 3D Laser Scanning -- From an Automated Tripod towards Optimal 3D Point Clouds from Mobile Laser Scanning. Nüchter, A.; Elseberg, J.; Borrmann, D. In GIM International, 27(9). 2013.
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  @article{GIM2013, author = {N{\"u}chter, A. and Elseberg, J. and Borrmann, D.}, journal = {GIM International}, keywords = {imported}, month = {09}, number = 9, title = {{Automation in 3D Laser Scanning – From an Automated Tripod towards Optimal 3D Point Clouds from Mobile Laser Scanning}}, volume = 27, year = 2013 }
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  On-Site Semantic mapping of Archeological Excavation Areas. Houshiar, H.; Borrmann, D.; Elseberg, J.; Nüchter, A.; Winkler, S.; Näth, F. In Proceedings of the XXIV International CIPA Symposium, of ISPRS Annals Photogrammetry and Remote Sensing. Spatial Inf. Sci., II-5/W1, pp. 163–168. Strasbourg, France, 2013.
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  3D laser scanning is the state of the art in modeling archaeological excavation sites, historical sites and even entire cities or landscapes. The documentation of findings on an excavation site is an essential archaeological task. Automated systems accelerate this process and decrease the amount of error to a minimum. This paper presents a new documentation approach in industrial archaeology. It consists of a set of tools for recording and registering 3D data from excavation sites. We provide an efficient tool for visualization of acquired 3D point clouds in 3D and 2D modes. The main purpose of this software is to provide an easy to use, on-site semantic mapping tool for archaeologists. It includes functions for selecting and labeling findings. Additional information can be provided for each label. This data is exported to an XML format and serves as input for other systems and databases.

  @inproceedings{CIPA2013, abstract = {3D laser scanning is the state of the art in modeling archaeological excavation sites, historical sites and even entire cities or landscapes. The documentation of findings on an excavation site is an essential archaeological task. Automated systems accelerate this process and decrease the amount of error to a minimum. This paper presents a new documentation approach in industrial archaeology. It consists of a set of tools for recording and registering 3D data from excavation sites. We provide an efficient tool for visualization of acquired 3D point clouds in 3D and 2D modes. The main purpose of this software is to provide an easy to use, on-site semantic mapping tool for archaeologists. It includes functions for selecting and labeling findings. Additional information can be provided for each label. This data is exported to an XML format and serves as input for other systems and databases.}, address = {Strasbourg, France}, author = {Houshiar, H. and Borrmann, D. and Elseberg, J. and N{\"u}chter, A. and Winkler, S. and N{\"a}th, F.}, booktitle = {Proceedings of the XXIV International CIPA Symposium}, keywords = {myown}, month = {09}, pages = {163–168}, series = {ISPRS Annals Photogrammetry and Remote Sensing. Spatial Inf. Sci., II-5/W1}, title = {{On-Site Semantic mapping of Archeological Excavation Areas}}, year = 2013 }
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  Multiple Vehicle-like Target Tracking Based on Velodyne Lidar. Zhang, Liang; Li, Qingquan; Li, Ming; Mao, Q.Zh; Nüchter, A. In Proceedings of the 6th IFAC Symposium on Intelligent Autonomous Vehicles (IAV ’13), Vol. 8. Gold Coast, Australia, 2013.
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  This paper proposes a novel multiple vehicle-like target tracking method based on a Velodyne HDL64E light detection and ranging (LiDAR) system. The proposed method combines multiple hypothesis tracking (MHT) algorithm with dynamic point cloud registration (DPCR), which is able to solve the multiple vehicle-like target tracking in highly dynamic urban environments without any auxiliary information from GPS or IMU. Specifically, to track targets consistently, the DPCR is developed to calculate accurately the pose of the ego-vehicle for the transformation of raw measurements taken in the moving coordinate systems into a static absolute coordinate system; while in turn, MHT helps to improve the performance of DPCR by discriminating and removing the dynamic points from the scene. Furthermore, the proposed MHT method is also able to solve the occlusion problem existing in the point cloud. Experiments on sets of urban environments prove that the presented method is effective and robust, even in highly dynamic environments.

  @inproceedings{IAV2013, abstract = {This paper proposes a novel multiple vehicle-like target tracking method based on a Velodyne HDL64E light detection and ranging (LiDAR) system. The proposed method combines multiple hypothesis tracking (MHT) algorithm with dynamic point cloud registration (DPCR), which is able to solve the multiple vehicle-like target tracking in highly dynamic urban environments without any auxiliary information from GPS or IMU. Specifically, to track targets consistently, the DPCR is developed to calculate accurately the pose of the ego-vehicle for the transformation of raw measurements taken in the moving coordinate systems into a static absolute coordinate system; while in turn, MHT helps to improve the performance of DPCR by discriminating and removing the dynamic points from the scene. Furthermore, the proposed MHT method is also able to solve the occlusion problem existing in the point cloud. Experiments on sets of urban environments prove that the presented method is effective and robust, even in highly dynamic environments.}, address = {Gold Coast, Australia}, author = {Zhang, Liang and Li, Qingquan and Li, Ming and Mao, Q.Zh and N{\"u}chter, A.}, booktitle = {Proceedings of the 6th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '13)}, keywords = {myown}, month = {06}, number = 1, title = {{Multiple Vehicle-like Target Tracking Based on Velodyne Lidar}}, volume = 8, year = 2013 }
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  One Billion Points in the Cloud --- An Octree for Efficient Processing of 3D Laser Scans. Elseberg, J.; Borrmann, D.; Nüchter, A. In ISPRS Journal of Photogrammetry \& Remote Sensing (JPRS), Special issue on terrestrial 3D modelling, 76, pp. 76–88. 2013.
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  Automated 3-dimensional modeling pipelines include 3D scanning, registration, data abstraction, and visualization. All steps in such a pipeline require the processing of a massive amount of 3D data, due to the ability of current 3D scanners to sample environments with a high density. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling these data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for an exchange file format, fast point cloud visualization, sped-up 3D scan matching, and shape detection algorithms. We evaluate our approach using typical terrestrial laser scans.

  @article{ISPRS2013, abstract = {Automated 3-dimensional modeling pipelines include 3D scanning, registration, data abstraction, and visualization. All steps in such a pipeline require the processing of a massive amount of 3D data, due to the ability of current 3D scanners to sample environments with a high density. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling these data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for an exchange file format, fast point cloud visualization, sped-up 3D scan matching, and shape detection algorithms. We evaluate our approach using typical terrestrial laser scans.}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, journal = {ISPRS Journal of Photogrammetry \& Remote Sensing (JPRS), Special issue on terrestrial 3D modelling}, keywords = {myown}, month = {02}, pages = {76–88}, title = {{One Billion Points in the Cloud — An Octree for Efficient Processing of 3D Laser Scans}}, volume = 76, year = 2013 }
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  Optimale 3D-Punktwolken aus mobilen Laserscandaten. Nüchter, A.; Elseberg, J.; Borrmann, D. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2013, Jade Hochschule, pp. 186–193. 2013.
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  Mobiles Laserscanning stellt hohe Anforderungen an die Exaktheit der Positionierung und Kalibrierung des Messsystems, da sich bereits kleinste Ungenauigkeiten in den akquirierten 3D-Daten drastisch niederschlagen können. Dieser Beitrag präsentiert eine neuen Ansatz zur Kalibrierung und zur Lösung des SLAM-Problems mit dem Ziel, die Messgenauigkeit des mobilen Scansystems zu optimieren. Bei dem Kalibrierungsverfahren handelt es sich um eine allgemeingültige Methode, die die Positionierung und Orientierung sämtlicher Sensoren berechnet, einschliesslich der Odometrie. Der vorgestellte SLAM-Ansatz (Simultaneous Localization and Mapping) ist semi-rigide. Dabei wird die Trajektorie so deformiert und jede Pose dahingehend optimiert, dass die Gesamtqualität der 3D-Punktwolke optimal wird. Das SLAM-Verfahren kann kurzfristige Sensorausfälle oder Ungenauigkeiten ausgleichen und ermöglicht vielfältige neue Anwendungen.

  @inproceedings{3DTAGE2013_2, abstract = {Mobiles Laserscanning stellt hohe Anforderungen an die Exaktheit der Positionierung und Kalibrierung des Messsystems, da sich bereits kleinste Ungenauigkeiten in den akquirierten 3D-Daten drastisch niederschlagen k{\"o}nnen. Dieser Beitrag pr{\"a}sentiert eine neuen Ansatz zur Kalibrierung und zur L{\"o}sung des SLAM-Problems mit dem Ziel, die Messgenauigkeit des mobilen Scansystems zu optimieren. Bei dem Kalibrierungsverfahren handelt es sich um eine allgemeing{\"u}ltige Methode, die die Positionierung und Orientierung s{\"a}mtlicher Sensoren berechnet, einschliesslich der Odometrie. Der vorgestellte SLAM-Ansatz (Simultaneous Localization and Mapping) ist semi-rigide. Dabei wird die Trajektorie so deformiert und jede Pose dahingehend optimiert, dass die Gesamtqualit{\"a}t der 3D-Punktwolke optimal wird. Das SLAM-Verfahren kann kurzfristige Sensorausf{\"a}lle oder Ungenauigkeiten ausgleichen und erm{\"o}glicht vielf{\"a}ltige neue Anwendungen.}, author = {N{\"u}chter, A. and Elseberg, J. and Borrmann, D.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2013, Jade Hochschule}, keywords = {imported}, month = {02}, pages = {186–193}, title = {{Optimale 3D-Punktwolken aus mobilen Laserscandaten}}, year = 2013 }
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  Panorama Based Point Cloud Reduction and Registration. Houshiar, H.; Elseberg, J.; Borrmann, D.; Nüchter, A. In Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR ’13), pp. 1–8. Montevideo, Uruguay, 2013.
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  To reconstruct environments 3D point clouds acquired by laser scanners are registered. This is an important but also time consuming part of any mapping system for mobile robots. The time needed for mapping is drastically reduced when the size of the input data is reduced. This paper examines different ways of reducing the size of point clouds without losing vital information for the matching process. We present novel point cloud reduction methods on the basis of panorama images. It is shown that the reduced point clouds are ideally suited for feature based registration on panorama images. We evaluate the presented reduction methods based on their effect on the performance of the registration algorithm.

  @inproceedings{ICAR2013_3, abstract = {To reconstruct environments 3D point clouds acquired by laser scanners are registered. This is an important but also time consuming part of any mapping system for mobile robots. The time needed for mapping is drastically reduced when the size of the input data is reduced. This paper examines different ways of reducing the size of point clouds without losing vital information for the matching process. We present novel point cloud reduction methods on the basis of panorama images. It is shown that the reduced point clouds are ideally suited for feature based registration on panorama images. We evaluate the presented reduction methods based on their effect on the performance of the registration algorithm.}, address = {Montevideo, Uruguay}, author = {Houshiar, H. and Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13)}, keywords = {myown}, month = 11, pages = {1–8}, title = {{Panorama Based Point Cloud Reduction and Registration}}, year = 2013 }
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  General Purpose Computing on Graphics Processing Units for Robotic Applications. B\ke}dkowski, J.; Majek, K.; Nüchter, A. In Journal of Software Engineering for Robotics (JOSER), 4(1), pp. 23–33. 2013.
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  This paper deals with research related with the improvements of state of the art algorithms used in robotic applications based on parallel computation. The main goal is to decrease the computational complexity of 3D cloud of points processing in such applications as: data filtering, normal vector estimation, data registration and calculation of point feature histogram. The presented results efficiently improve the existing implementations with minimal lost of accuracy. The main contribution is a regular grid decomposition originally implemented for nearest neighborhood search. This data structure is used almost for all presented methods, it provides an efficient method for decreasing the time of computation. The results are compared with well-known robotic frameworks such as PCL and 3DTK.

  @article{JOSER2013, abstract = {This paper deals with research related with the improvements of state of the art algorithms used in robotic applications based on parallel computation. The main goal is to decrease the computational complexity of 3D cloud of points processing in such applications as: data filtering, normal vector estimation, data registration and calculation of point feature histogram. The presented results efficiently improve the existing implementations with minimal lost of accuracy. The main contribution is a regular grid decomposition originally implemented for nearest neighborhood search. This data structure is used almost for all presented methods, it provides an efficient method for decreasing the time of computation. The results are compared with well-known robotic frameworks such as PCL and 3DTK.}, author = {B\k{e}dkowski, J. and Majek, K. and N{\"u}chter, A.}, journal = {Journal of Software Engineering for Robotics (JOSER)}, keywords = {imported}, number = 1, pages = {23–33}, title = {{General Purpose Computing on Graphics Processing Units for Robotic Applications}}, volume = 4, year = 2013 }
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  Sliced Curvature Scale Space for Representing and Recognizing 3D Object. Okal, B.; Nüchter, A. In Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR ’13), pp. 1–7. Montevideo, Uruguay, 2013.
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  Perception plays a key role in the development of intelligent autonomous systems. In particular object recognition and registration tasks are crucial to any intelligent autonomous system such as autonomous cars or personal robots. The representation of 3D object sensor measurements largely affects the choice of higher level processing possible on the sensor data. We explore the use of scale space theory via the curvature scale space and extend it to represent 3D objects in our new SCSS (Sliced Curvature Scale Space) framework. We further develop techniques of further processing the SCSS representation including feature extraction and dimensionality reduction for use in learning frameworks. We perform an array of experiments to validate the effectiveness of our method and demonstrate recognition performance using support vector machines. The results indicate that our new representation retains the nice qualities of the original curvature scale space method while being robust and compact for 3D object representation and recognition.

  @inproceedings{ICAR2013_2, abstract = {Perception plays a key role in the development of intelligent autonomous systems. In particular object recognition and registration tasks are crucial to any intelligent autonomous system such as autonomous cars or personal robots. The representation of 3D object sensor measurements largely affects the choice of higher level processing possible on the sensor data. We explore the use of scale space theory via the curvature scale space and extend it to represent 3D objects in our new SCSS (Sliced Curvature Scale Space) framework. We further develop techniques of further processing the SCSS representation including feature extraction and dimensionality reduction for use in learning frameworks. We perform an array of experiments to validate the effectiveness of our method and demonstrate recognition performance using support vector machines. The results indicate that our new representation retains the nice qualities of the original curvature scale space method while being robust and compact for 3D object representation and recognition.}, address = {Montevideo, Uruguay}, author = {Okal, B. and N{\"u}chter, A.}, booktitle = {Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13)}, keywords = {imported}, month = 11, pages = {1–7}, title = {{Sliced Curvature Scale Space for Representing and Recognizing 3D Object}}, year = 2013 }
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  A Study of Scan Patterns for Mobile Mapping. Elseberg, J.; Borrmann, D.; Nüchter., A. In Proceedings of the ISPRS Conference on "Serving Society with Geoinformatics" (ISPRS-SSG ’13), of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-7/W2, pp. 75–80. Antalya, Turkey, 2013.
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  Mobile terrestrial scanning systems automate terrestrial laser scanning. Continous scanning mobile terrestrial systems constantly spin the terrestrial laser scanner and thus combine terrestrial scanning with kinematic laser scanning. This paper presents a scan pattern analysis for these systems. We aim at finding the most advantageous combination of terrestrial and kinematic systems. The resulting 3D point cloud depends on the scan pattern and the trajectory and velocity of the mobile system.

  @inproceedings{SSG2013, abstract = {Mobile terrestrial scanning systems automate terrestrial laser scanning. Continous scanning mobile terrestrial systems constantly spin the terrestrial laser scanner and thus combine terrestrial scanning with kinematic laser scanning. This paper presents a scan pattern analysis for these systems. We aim at finding the most advantageous combination of terrestrial and kinematic systems. The resulting 3D point cloud depends on the scan pattern and the trajectory and velocity of the mobile system.}, address = {Antalya, Turkey}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter., A.}, booktitle = {Proceedings of the ISPRS Conference on "Serving Society with Geoinformatics" (ISPRS-SSG '13)}, keywords = {imported}, month = 11, pages = {75–80}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-7/W2}, title = {A Study of Scan Patterns for Mobile Mapping}, year = 2013 }
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  Point Guards and Point Clouds: Solving general Art Gallery Problems. Borrmann, D.; de Rezende, P. J.; de Souza, C. C.; Fekete, S. P.; Friedrich, S.; Kröller, A.; Nüchter, A.; Schmidt, C.; Tozoni, D. C. In Proccedings of the 20th ACM Annual Symposium on Computational Geometry (SoCG ’13), pp. 347–348. Rio de Janeiro, Brazil, 2013.
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  In this video, we illustrate how one of the classical areas of computational geometry has gained in practical relevance, which in turn gives rise to new, fascinating geometric problems. In particular, we demonstrate how the robot platform IRMA3D can produce high-resolution, virtual 3D environments, based on a limited number of laser scans. Computing an optimal set of scans amounts to solving an instance of the Art Gallery Problem (AGP): Place a minimum number of stationary guards in a polygonal region P, such that all points in P are guarded.

  @inproceedings{SOCG2013, abstract = {In this video, we illustrate how one of the classical areas of computational geometry has gained in practical relevance, which in turn gives rise to new, fascinating geometric problems. In particular, we demonstrate how the robot platform IRMA3D can produce high-resolution, virtual 3D environments, based on a limited number of laser scans. Computing an optimal set of scans amounts to solving an instance of the Art Gallery Problem (AGP): Place a minimum number of stationary guards in a polygonal region P, such that all points in P are guarded.}, address = {Rio de Janeiro, Brazil}, author = {Borrmann, D. and de Rezende, P. J. and de Souza, C. C. and Fekete, S. P. and Friedrich, S. and Kr{\"o}ller, A. and N{\"u}chter, A. and Schmidt, C. and Tozoni, D. C.}, booktitle = {Proccedings of the 20th ACM Annual Symposium on Computational Geometry (SoCG '13)}, keywords = {imported}, month = {06}, pages = {347–348}, title = {{Point Guards and Point Clouds: Solving general Art Gallery Problems}}, year = 2013 }
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  Interior Reconstruction using the 3D Hough Transform. Dumitru, R.-C.; Borrmann, D.; Nüchter, A. In Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2013: "3D Virtual Reconstruction and Visualization of Complex Architectures", of ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-5/W1. Trento, Italy, 2013.
  • [ Abstract ]
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  Laser scanners are often used to create accurate 3D models of buildings for civil engineering purposes, but the process of manually vectorizing a 3D point cloud is time consuming and error-prone (Adan and Huber, 2011). Therefore, the need to characterize and quantify complex environments in an automatic fashion arises, posing challenges for data analysis. This paper presents a system for 3D modeling by detecting planes in 3D point clouds, based on which the scene is reconstructed at a high architectural level through removing automatically clutter and foreground data. The implemented software detects openings, such as windows and doors and completes the 3D model by inpainting.

  @inproceedings{3DARCH2013, abstract = {Laser scanners are often used to create accurate 3D models of buildings for civil engineering purposes, but the process of manually vectorizing a 3D point cloud is time consuming and error-prone (Adan and Huber, 2011). Therefore, the need to characterize and quantify complex environments in an automatic fashion arises, posing challenges for data analysis. This paper presents a system for 3D modeling by detecting planes in 3D point clouds, based on which the scene is reconstructed at a high architectural level through removing automatically clutter and foreground data. The implemented software detects openings, such as windows and doors and completes the 3D model by inpainting.}, address = {Trento, Italy}, author = {Dumitru, R.-C. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the 5th ISPRS International Workshop 3D-ARCH 2013: "3D Virtual Reconstruction and Visualization of Complex Architectures"}, keywords = {imported}, month = {02}, series = {ISPRS Archives Photogrammetry and Remote Senssing Spatial Inf. Sci., Volume XL-5/W1}, title = {{Interior Reconstruction using the 3D Hough Transform}}, year = 2013 }
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  Irma3D -- An Intelligent Robot for Mapping Applications. Nüchter, A.; Elseberg, J.; Borrmann, D. In Proceedings of the 3rd IFAC Symposium on Telematics Applications (TA ’13), pp. 119–124. Seoul, Korea, 2013.
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  Motivated by the increasing need of rapid characterization of environments in 3D, we designed a robot system that automates the work of an operator of terrestrial laser scanners. The built system enables to work without using special targets or markers and thus enables the surveyors to save more than 75\% of the time spent in the field. Another impulse for developing the platform is the demand for a remote multi-sensor inspection tool. The robot is capable of surveying remote sites or danger areas, such as plants, underground mines, tunnels, caves, or channels. The results are precise, multi-modal digital 3D maps. This paper presents the recently developed robot Irma3D, its hardware, the developed interconnected software modules, the associated sensor calibration methods and a few applications.

  @inproceedings{TA2013, abstract = {Motivated by the increasing need of rapid characterization of environments in 3D, we designed a robot system that automates the work of an operator of terrestrial laser scanners. The built system enables to work without using special targets or markers and thus enables the surveyors to save more than 75\% of the time spent in the field. Another impulse for developing the platform is the demand for a remote multi-sensor inspection tool. The robot is capable of surveying remote sites or danger areas, such as plants, underground mines, tunnels, caves, or channels. The results are precise, multi-modal digital 3D maps. This paper presents the recently developed robot Irma3D, its hardware, the developed interconnected software modules, the associated sensor calibration methods and a few applications.}, address = {Seoul, Korea}, author = {N{\"u}chter, A. and Elseberg, J. and Borrmann, D.}, booktitle = {Proceedings of the 3rd IFAC Symposium on Telematics Applications (TA '13)}, keywords = {imported}, month = 11, pages = {119–124}, title = {{Irma3D – An Intelligent Robot for Mapping Applications}}, year = 2013 }
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  Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency. Demisse, G.; Borrmann, D.; Nüchter, A. In Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR ’13), pp. 1–8. Montevideo, Uruguay, 2013.
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  In recent years, 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited, because most models are pure representations with no or little associated semantics. In this paper, we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Furthermore, a Markov Random Field is used to model the temperature distribution of detected windows to further label the windows as either open, closed or damaged.

  @inproceedings{ICAR2013_1, abstract = {In recent years, 3D models of buildings are used in maintenance and inspection, preservation, and other building related applications. However, the usage of these models is limited, because most models are pure representations with no or little associated semantics. In this paper, we present a pipeline of techniques used for interior interpretation, object detection, and adding energy related semantics to windows of a 3D thermal model. A sequence of algorithms is presented for building the fundamental semantics of a 3D model. Furthermore, a Markov Random Field is used to model the temperature distribution of detected windows to further label the windows as either open, closed or damaged.}, address = {Montevideo, Uruguay}, author = {Demisse, G. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the 16th IEEE International Conference on Advanced Robotics (ICAR '13)}, keywords = {imported}, month = 11, pages = {1–8}, title = {{Interpreting Thermal 3D Models of Indoor Environments for Energy Efficiency}}, year = 2013 }

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  Mixed Palletizing and Task Completion for Virtual Warehouses. Demisse, G.; Mihalyi, R.; Okal, B.; Poudel, D.; Schauer, J.; Nüchter, A. In Virtual Manufacturing Automation (VMAC ’12) Workshop at IEEE International Conference Robotics and Automation, ICRA. St. Paul, MN, USA, 2012.
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  Palletizing, or packing rectangular boxes of various sizes onto pallets, is a frequently encountered task in many commercial scenarios, e.g., shipment of goods. An extension of this problem is the automated placement of boxes on pallets, henceforth task completion, by means of industrial robot arms. The palletizing and task completion problems are treated in the context of the IEEE ICRA 2012 Virtual Manufacturing Automation Competition. We approach the palletizing challenge by a winner-takes-all strategy, where multiple heuristics are evaluated against the given datasets. Our results show a performance comparable to that of the commercial software benchmark from the previous competitions. We solve task completion in USARSim by picking boxes and placing them on a pallet. Our inverse kinematics algorithm consists of a geometric and numeric component.

  @inproceedings{VMAC2012, abstract = {Palletizing, or packing rectangular boxes of various sizes onto pallets, is a frequently encountered task in many commercial scenarios, e.g., shipment of goods. An extension of this problem is the automated placement of boxes on pallets, henceforth task completion, by means of industrial robot arms. The palletizing and task completion problems are treated in the context of the IEEE ICRA 2012 Virtual Manufacturing Automation Competition. We approach the palletizing challenge by a winner-takes-all strategy, where multiple heuristics are evaluated against the given datasets. Our results show a performance comparable to that of the commercial software benchmark from the previous competitions. We solve task completion in USARSim by picking boxes and placing them on a pallet. Our inverse kinematics algorithm consists of a geometric and numeric component.}, address = {St. Paul, MN, USA}, author = {Demisse, G. and Mihalyi, R. and Okal, B. and Poudel, D. and Schauer, J. and N{\"u}chter, A.}, booktitle = {Virtual Manufacturing Automation (VMAC '12) Workshop at IEEE International Conference Robotics and Automation, ICRA}, keywords = {imported}, month = {05}, title = {Mixed Palletizing and Task Completion for Virtual Warehouses}, year = 2012 }
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  Robust Registration of Narrow-Field-of-View Range Images. May, S.; Koch, R.; Scherlipp, R.; Nüchter, A. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO ’12), Vol. 10. Dubrovnik, Croatia, 2012.
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  This paper focuses on range image registration for robot localization and environment mapping. It extends the well-known Iterative Closest Point (ICP) algorithm in order to deal with erroneous measurements. The dealing with measurement errors originating from external lighting, occlusions or limitations in the measurement range is only rudimentary in literature. In this context we present a non-parametric extension to the ICP algorithm that is derived directly from measurement modalities of sensors in projective space. We show how aspects from reverse calibration can be embedded in search-tree-based approaches. Experiments demonstrate the applicability to range sensors like the Kinect device, Time-of-Flight cameras and 3D laser range finders. As a result the image registration becomes faster and more robust.

  @inproceedings{SYROCO2012_2, abstract = {This paper focuses on range image registration for robot localization and environment mapping. It extends the well-known Iterative Closest Point (ICP) algorithm in order to deal with erroneous measurements. The dealing with measurement errors originating from external lighting, occlusions or limitations in the measurement range is only rudimentary in literature. In this context we present a non-parametric extension to the ICP algorithm that is derived directly from measurement modalities of sensors in projective space. We show how aspects from reverse calibration can be embedded in search-tree-based approaches. Experiments demonstrate the applicability to range sensors like the Kinect device, Time-of-Flight cameras and 3D laser range finders. As a result the image registration becomes faster and more robust.}, address = {Dubrovnik, Croatia}, author = {May, S. and Koch, R. and Scherlipp, R. and N{\"u}chter, A.}, booktitle = {Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12)}, keywords = {imported}, month = {09}, title = {{Robust Registration of Narrow-Field-of-View Range Images}}, volume = 10, year = 2012 }
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  Dynamic VeloSLAM -- Preliminary Report on 3D Mapping of Dynamic Environments. Li, Ming; Li, Wei; Wang, Jian; Li, Qingquan; Nüchter, A. In Proceedings of the 2012 IEEE Intelligent Vehicles Symposium (IV ’12), Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles. Alcala de Henares, Madrid, Spain, 2012.
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  3D mapping using point cloud registration is a basic inevitable problem for many applications, especially for modeling of large scale complicated environments. This paper presents a novel approach for mapping highly dynamic environments, i.e., we present a system capable for mapping road traffic scenarios. Given 3D laser scans acquired at a high frame rate and no other sensor input, a 3D map is built by removing dynamic parts of the scene and estimating the ego-motion of the vehicle precisely at the same time. We extend the well-known ICP algorithm for HDL-64 laser scan data and build a system for solving the simultaneous localization and mapping problem in urban road scenarios. This paper presents initial results on two data sets.

  @inproceedings{IV2012_WS, abstract = {3D mapping using point cloud registration is a basic inevitable problem for many applications, especially for modeling of large scale complicated environments. This paper presents a novel approach for mapping highly dynamic environments, i.e., we present a system capable for mapping road traffic scenarios. Given 3D laser scans acquired at a high frame rate and no other sensor input, a 3D map is built by removing dynamic parts of the scene and estimating the ego-motion of the vehicle precisely at the same time. We extend the well-known ICP algorithm for HDL-64 laser scan data and build a system for solving the simultaneous localization and mapping problem in urban road scenarios. This paper presents initial results on two data sets.}, address = {Alcala de Henares, Madrid, Spain}, author = {Li, Ming and Li, Wei and Wang, Jian and Li, Qingquan and N{\"u}chter, A.}, booktitle = {Proceedings of the 2012 IEEE Intelligent Vehicles Symposium (IV '12), Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles}, keywords = {myown}, month = {06}, title = {Dynamic VeloSLAM – Preliminary Report on 3D Mapping of Dynamic Environments}, year = 2012 }
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  Ein Punkt pro Kubikmeter -- präzise Registrierung von terrestrischen Laserscans mit Scanmatching. Borrmann, D.; Elseberg, J.; K.C., P. N.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2012, Jade Hochschule, pp. 4–11. 2012.
  • [ Abstract ]
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  Die präzise Registrierung von terrestrischen Laserscans erfordert geschultes Personal, professionelle Scanner Hardware, meist proprietäre Software sowie genügend Zeit für die Anbringung von Zielmarken, Durchführung der Messungen und die anschlie&szilg;ende Verarbeitung der akquirierten Daten. Wir zeigen, wie man auf einige dieser Punkte verzichten und dennoch zu hochqualitativen Ergebnissen kommen kann. Im Zuge einer Bachelorarbeit wurde ein der Vermessungstechnik fremder Informatikstudent damit beauftragt, den Campus der Jacobs University auf einer Teilfläche von ca. 9 ha zu vermessen. Zur Verfügung standen ein professioneller Scanner in Form des Riegl VZ-400. Insgesamt wurden 131 Aufnahmen mit insgesamt über 2 Milliarden Punkten gemacht. Nach manueller Vorregistrierung der Punktwolken erfolgte die präzise Anordnung dann vollautomatisch mit der frei erhältlichen Software 3DTK, die dazu in der Lage war die gesamte Datenmenge in kürzester Zeit mit höchster Genauigkeit zu registrieren.

  @inproceedings{3DTAGE2012_1, abstract = {Die präzise Registrierung von terrestrischen Laserscans erfordert geschultes Personal, professionelle Scanner Hardware, meist proprietäre Software sowie genügend Zeit für die Anbringung von Zielmarken, Durchführung der Messungen und die anschlie&szilg;ende Verarbeitung der akquirierten Daten. Wir zeigen, wie man auf einige dieser Punkte verzichten und dennoch zu hochqualitativen Ergebnissen kommen kann. Im Zuge einer Bachelorarbeit wurde ein der Vermessungstechnik fremder Informatikstudent damit beauftragt, den Campus der Jacobs University auf einer Teilfläche von ca. 9 ha zu vermessen. Zur Verfügung standen ein professioneller Scanner in Form des Riegl VZ-400. Insgesamt wurden 131 Aufnahmen mit insgesamt über 2 Milliarden Punkten gemacht. Nach manueller Vorregistrierung der Punktwolken erfolgte die präzise Anordnung dann vollautomatisch mit der frei erhältlichen Software 3DTK, die dazu in der Lage war die gesamte Datenmenge in kürzester Zeit mit höchster Genauigkeit zu registrieren.}, author = {Borrmann, D. and Elseberg, J. and K.C., P. N. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2012, Jade Hochschule}, keywords = {imported}, month = {02}, pages = {4–11}, title = {{Ein Punkt pro Kubikmeter – pr{\"a}zise Registrierung von terrestrischen Laserscans mit Scanmatching}}, year = 2012 }
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  Mobile Roboter: Eine Einführung aus Sicht der Informatik. Hertzberg, J.; Lingemann, K.; Nüchter, A. In of eXamen.press, p. 390. Springer, Heidelberg, Germany, 2012.
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  @book{Lehrbuch_2012, address = {Heidelberg, Germany}, author = {Hertzberg, J. and Lingemann, K. and N{\"u}chter, A.}, keywords = {myown}, pages = 390, publisher = {Springer}, series = {eXamen.press}, title = {{Mobile Roboter: Eine Einf{\"u}hrung aus Sicht der Informatik}}, year = 2012 }
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  Eine Milliarde 3D-Punkte mit Standardhardware verarbeiten -- Processing One Billion 3D Points on a Standard Computer. Elseberg, J.; Borrmann, D.; Nüchter, A. In Allgemeine Vermessungs-Nachrichten (AVN), 119(1), pp. 11–23. 2012.
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  Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor. Sie ermöglicht es, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repräsentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, grosse Punktwolken zu inspizieren und flüssig in ihnen zu navigieren. Des Weiteren schlagen wir in diesem Artikel ein effizentes binäres Dateiformat für den Austausch von 3D-Scans vor.

  @article{AVN2012, abstract = {Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor. Sie ermöglicht es, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repräsentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, grosse Punktwolken zu inspizieren und flüssig in ihnen zu navigieren. Des Weiteren schlagen wir in diesem Artikel ein effizentes binäres Dateiformat für den Austausch von 3D-Scans vor.}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, journal = {Allgemeine Vermessungs-Nachrichten (AVN)}, keywords = {imported}, month = {01}, number = 1, pages = {11–23}, title = {{Eine Milliarde 3D-Punkte mit Standardhardware verarbeiten – Processing One Billion 3D Points on a Standard Computer}}, volume = 119, year = 2012 }
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  Comparison on nearest-neigbour-search strategies and implementations for efficient shape registration. Elseberg, J.; Magnenat, S.; Siegwart, R.; Nüchter, A. In Journal of Software Engineering for Robotics (JOSER), 3(1), pp. 2–12. 2012.
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  The iterative closest point (icp) algorithm is one of the most popular approaches to shape registration currently in use. At the core of icp is the computationally-intensive determination of nearest neighbors (NN). As of now there has been no comprehensive analysis of competing search strategies for NN. This paper compares several libraries for nearest-neighbor search (NNS) on both simulated and real data with a focus on shape registration. In addition, we present a novel efficient implementation of NNS via k-d trees as well as a novel algorithm for NNS in octrees.

  @article{JOSER2012, abstract = {The iterative closest point (icp) algorithm is one of the most popular approaches to shape registration currently in use. At the core of icp is the computationally-intensive determination of nearest neighbors (NN). As of now there has been no comprehensive analysis of competing search strategies for NN. This paper compares several libraries for nearest-neighbor search (NNS) on both simulated and real data with a focus on shape registration. In addition, we present a novel efficient implementation of NNS via k-d trees as well as a novel algorithm for NNS in octrees.}, author = {Elseberg, J. and Magnenat, S. and Siegwart, R. and N{\"u}chter, A.}, journal = {Journal of Software Engineering for Robotics (JOSER)}, keywords = {myown}, number = 1, pages = {2–12}, title = {Comparison on nearest-neigbour-search strategies and implementations for efficient shape registration}, volume = 3, year = 2012 }
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  Projektionen für die Scanregistrierung mit Hilfe von Bildmerkmalen. Nüchter, A.; Houshair, H.; Borrmann, D.; Elseberg, J. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2012, Jade Hochschule, pp. 12–21. 2012.
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  Die Aufnahme und das Registrieren von terrestrischen 3D-Laserscans ist eine grundlegende Fragestellung in vielen Anwendungsbereichen. Um den Prozess des Registrierens von zwei 3D-Scans zu automatisieren, werden Merkmale aus den Scandaten extrahiert, diese einander zugeordnet (assoziiert) und die Registrierung berechnet. Als Merkmale kommen neben Strukturmerkmalen wie 3D-Flächen oft Bildmerkmale zum Einsatz. Dazu wird ein flächiges Bild der Reflektionswerte eines 3D-Scans erzeugt. In der Regel wird hierbei auf der x-Achse der Rotationswinkel um die Stehachse des Scanners und auf der y-Achse der Rotationswinkel des Spiegels abgetragen. In diesem Beitrag untersuchen wir wie sich die Registrierungsergebnisse ändern, wenn andere Projektionen verwendet werden. Dazu analysieren wir mit Hilfe von SIFT-Merkmalen die gleichmäßige Rektangularprojektion, die zylindrische Projektion, die Hochachsenrojektion, die Mercatorprojektion, die Rektangularprojektion, die Pannini-Projektion, sowie die stereographische Projektion.

  @inproceedings{3DTAGE2012_2, abstract = {Die Aufnahme und das Registrieren von terrestrischen 3D-Laserscans ist eine grundlegende Fragestellung in vielen Anwendungsbereichen. Um den Prozess des Registrierens von zwei 3D-Scans zu automatisieren, werden Merkmale aus den Scandaten extrahiert, diese einander zugeordnet (assoziiert) und die Registrierung berechnet. Als Merkmale kommen neben Strukturmerkmalen wie 3D-Flächen oft Bildmerkmale zum Einsatz. Dazu wird ein flächiges Bild der Reflektionswerte eines 3D-Scans erzeugt. In der Regel wird hierbei auf der x-Achse der Rotationswinkel um die Stehachse des Scanners und auf der y-Achse der Rotationswinkel des Spiegels abgetragen. In diesem Beitrag untersuchen wir wie sich die Registrierungsergebnisse ändern, wenn andere Projektionen verwendet werden. Dazu analysieren wir mit Hilfe von SIFT-Merkmalen die gleichmäßige Rektangularprojektion, die zylindrische Projektion, die Hochachsenrojektion, die Mercatorprojektion, die Rektangularprojektion, die Pannini-Projektion, sowie die stereographische Projektion.}, author = {N{\"u}chter, A. and Houshair, H. and Borrmann, D. and Elseberg, J.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2012, Jade Hochschule}, keywords = {imported}, month = {02}, pages = {12–21}, title = {{Projektionen f{\"u}r die Scanregistrierung mit Hilfe von Bildmerkmalen}}, year = 2012 }
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  3D LIDAR Point Cloud based Intersection Recognition for Autonomous Driving. Chen, Long; Li, Qingquan; Zhu, Quanwen; Li, Ming; Nüchter, A. In Proceedings of the 2012 IEEE Intelligent Vehicles Symposium (IV ’12), pp. 456–461. Alcala de Henares, Madrid, Spain, 2012.
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  Finding road intersections in advance is crucial for navigation and path planning of moving autonomous vehicles, especially when there is no position or geographic auxiliary information available. In this paper, we investigate the use of a 3D point cloud based solution for intersection and road segment classification in front of an autonomous vehicle. It is based on the analysis of the features from the designed beam model. First, we build a grid map of the point cloud and clear the cells which belong to other vehicles. Then, the proposed beam model is applied with a specified distance in front of autonomous vehicle. A feature set based on the length distribution of the beam is extracted from the current frame and combined with a trained classifier to solve the road-type classification problem, i.e., segment and intersection. In addition, we also make the distinction between +-shaped and T-shaped intersections. The results are reported over a series of real-world data. A performance of above 80\% correct classification is reported at a real-time classification rate of 5 Hz.

  @inproceedings{IV2012, abstract = {Finding road intersections in advance is crucial for navigation and path planning of moving autonomous vehicles, especially when there is no position or geographic auxiliary information available. In this paper, we investigate the use of a 3D point cloud based solution for intersection and road segment classification in front of an autonomous vehicle. It is based on the analysis of the features from the designed beam model. First, we build a grid map of the point cloud and clear the cells which belong to other vehicles. Then, the proposed beam model is applied with a specified distance in front of autonomous vehicle. A feature set based on the length distribution of the beam is extracted from the current frame and combined with a trained classifier to solve the road-type classification problem, i.e., segment and intersection. In addition, we also make the distinction between +-shaped and T-shaped intersections. The results are reported over a series of real-world data. A performance of above 80\% correct classification is reported at a real-time classification rate of 5 Hz.}, address = {Alcala de Henares, Madrid, Spain}, author = {Chen, Long and Li, Qingquan and Zhu, Quanwen and Li, Ming and N{\"u}chter, A.}, booktitle = {Proceedings of the 2012 IEEE Intelligent Vehicles Symposium (IV '12)}, keywords = {imported}, month = {06}, pages = {456–461}, title = {{3D LIDAR Point Cloud based Intersection Recognition for Autonomous Driving}}, year = 2012 }
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  Automatic and Full Calibration of Mobile Laser Scanning Systems. J. Elseberg, D. Borrmann. In Proceedings of the 13th International Symposium of Experimental Robotics (ISER ’12), of Springer Tracts in Advanced Robotics, pp. 907–917. Quebec City, Canada, 2012.
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  Mobile scanning, i.e., the practice of mounting laser scanners on moving platforms is an efficient way to acquire accurate and dense 3D point clouds of outdoor environments for urban and regional planning and architecture. The mobile scenario puts high requirements on the accuracy of the calibration of the measurement system, as small calibration inaccuracies lead to large errors in the resulting point cloud. We propose a novel algorithm for the calibration of a mobile scanning system that estimates the calibration parameters for all sensor components simultaneously without relying on additional hardware. We evaluate the calibration algorithm on several real world data sets where ground truth is available via an accurate geodetic model.

  @inproceedings{ISER2012, abstract = {Mobile scanning, i.e., the practice of mounting laser scanners on moving platforms is an efficient way to acquire accurate and dense 3D point clouds of outdoor environments for urban and regional planning and architecture. The mobile scenario puts high requirements on the accuracy of the calibration of the measurement system, as small calibration inaccuracies lead to large errors in the resulting point cloud. We propose a novel algorithm for the calibration of a mobile scanning system that estimates the calibration parameters for all sensor components simultaneously without relying on additional hardware. We evaluate the calibration algorithm on several real world data sets where ground truth is available via an accurate geodetic model.}, address = {Quebec City, Canada}, author = {{J. Elseberg, D. Borrmann}, A. N{\"u}chter}, booktitle = {Proceedings of the 13th International Symposium of Experimental Robotics (ISER '12)}, keywords = {myown}, month = {06}, number = 88, pages = {907–917}, series = {Springer Tracts in Advanced Robotics}, title = {{Automatic and Full Calibration of Mobile Laser Scanning Systems}}, year = 2012 }
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  Thermal 3D Mapping of Building Facades. Borrmann, D.; Elseberg, J.; A, Nüchter. In Proceedings of the 8th Conference on Intelligent Autonomous Systems (IAS ’12), Vol. 2 of Advances in Intelligent Systems and Computing, pp. 173–182. Springer, Jeju Island, Korea, 2012.
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  Never before in history were humans as dependant on energy as we are today. But the natural ressources are limited and a waste of energy has drastic influences on the environment. In their Action Plan for Energy Efficiency [6] the European Commission estimates that the largest and cost-effictive energy savings potential lies in residential ($\sim$27\%) and commercial ($\sim$30\%) buildings. To eliminate heat and air conditioning losses in buildings and factories heat and air leaks need to be localized and identified. Imagine the availability of a complete 3D model of every building that architects can use to analyze the heat insulation of buildings and to identify necessary modifications. In these 3D models temperature peaks are not only detectable but also their extent is visible. A robot equiped with a 3D laser scanner, a thermal camera, and a color camera constitutes the basis for our approach. The data from all three sensors and from different locations are joined into one high-precise 3D model that shows the heat distribution. This paper describes the setup of the hardware and the methods applied to create the 3D model, including the automatic co-calibration of the sensors. Challenges unique to the task of thermal mapping of outdoor environments are discussed.

  @inproceedings{IAS2012, abstract = {Never before in history were humans as dependant on energy as we are today. But the natural ressources are limited and a waste of energy has drastic influences on the environment. In their Action Plan for Energy Efficiency [6] the European Commission estimates that the largest and cost-effictive energy savings potential lies in residential ($\sim$27\%) and commercial ($\sim$30\%) buildings. To eliminate heat and air conditioning losses in buildings and factories heat and air leaks need to be localized and identified. Imagine the availability of a complete 3D model of every building that architects can use to analyze the heat insulation of buildings and to identify necessary modifications. In these 3D models temperature peaks are not only detectable but also their extent is visible. A robot equiped with a 3D laser scanner, a thermal camera, and a color camera constitutes the basis for our approach. The data from all three sensors and from different locations are joined into one high-precise 3D model that shows the heat distribution. This paper describes the setup of the hardware and the methods applied to create the 3D model, including the automatic co-calibration of the sensors. Challenges unique to the task of thermal mapping of outdoor environments are discussed.}, address = {Jeju Island, Korea}, author = {Borrmann, D. and Elseberg, J. and A, N{\"u}chter}, booktitle = {Proceedings of the 8th Conference on Intelligent Autonomous Systems (IAS '12)}, keywords = {myown}, month = {06}, number = 192, pages = {173–182}, publisher = {Springer}, series = {Advances in Intelligent Systems and Computing}, title = {{Thermal 3D Mapping of Building Facades}}, volume = 2, year = 2012 }
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  Thermal 3D Modeling of Indoor Environments for Saving Energy. Borrmann, D.; Afzal, H.; Elseberg, J.; Nüchter, A. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’12), pp. 4538–4539. Vilamoura, Algarve, Portugal, 2012.
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  Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency [4] of the European Commission estimates that the largest cost-effective energy savings potential lies in residential ($\sim$27\%) and commercial ($\sim$30\%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This video presents our approach to this task. Methods for creating a consistent laser scan model enhanced with information from thermal and optical cameras are presented.

  @inproceedings{IROS2012Video, abstract = {Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency [4] of the European Commission estimates that the largest cost-effective energy savings potential lies in residential ($\sim$27\%) and commercial ($\sim$30\%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This video presents our approach to this task. Methods for creating a consistent laser scan model enhanced with information from thermal and optical cameras are presented.}, address = {Vilamoura, Algarve, Portugal}, author = {Borrmann, D. and Afzal, H. and Elseberg, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12)}, keywords = {imported}, month = 10, pages = {4538–4539}, title = {{Thermal 3D Modeling of Indoor Environments for Saving Energy}}, year = 2012 }
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  An extension of the Felzenszwalb-Huttenlocher segmentation to 3D point clouds. Sima, M.-C.; Nüchter, A. In Proceedings of the 5th International Conference on Machine Vision (ICMV ’12), of SPIE 8783. Wuhan, China, 2012.
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  This paper investigates the segmentation algorithm proposed by Felzenszwalb and Huttenlocher1 and its compatibility to 3D point clouds acquired with state-of-the-art 3D laser scanners. To use the algorithm, we adapt the range and intensity data to the smoothed graph structure used by the algorithm. We investigate the influence of the algorithm’s parameters to its performance and result that are meaningful to both the machines and the humans.

  @inproceedings{ICMV2012, abstract = {This paper investigates the segmentation algorithm proposed by Felzenszwalb and Huttenlocher1 and its compatibility to 3D point clouds acquired with state-of-the-art 3D laser scanners. To use the algorithm, we adapt the range and intensity data to the smoothed graph structure used by the algorithm. We investigate the influence of the algorithm’s parameters to its performance and result that are meaningful to both the machines and the humans.}, address = {Wuhan, China}, author = {Sima, M.-C. and N{\"u}chter, A.}, booktitle = {Proceedings of the 5th International Conference on Machine Vision (ICMV '12)}, keywords = {imported}, month = 10, series = {SPIE 8783}, title = {{An extension of the Felzenszwalb-Huttenlocher segmentation to 3D point clouds}}, year = 2012 }
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  The Project ThermalMapper -- Thermal 3D Mapping of Indoor Environments for Saving Energy. Borrmann, D.; Nüchter, A.; Dakulovic, M.; Maurovic, I.; Petrovic, I.; Osmankovic, D.; Velagic, J. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO ’12), Vol. 10. Dubrovnik, Croatia, 2012.
  • [ Abstract ]
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  Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency of the Commission of the European Communities (2008) estimates that the largest cost-effective energy savings potential lies in residential ($\sim$27\%) and commercial ($\sim$30\%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This paper presents our overall approach to map indoor environments with thermal data in 3D.

  @inproceedings{SYROCO2012_4, abstract = {Heat and air conditioning losses in buildings and factories lead to a large amount of wasted energy. The Action Plan for Energy Efficiency of the Commission of the European Communities (2008) estimates that the largest cost-effective energy savings potential lies in residential ($\sim$27\%) and commercial ($\sim$30\%) buildings. Imagine a technology that creates a precise digital 3D model of heat distribution and heat flow enabling one to detect all sources of wasted energy and to modify buildings to reach these savings. This paper presents our overall approach to map indoor environments with thermal data in 3D.}, address = {Dubrovnik, Croatia}, author = {Borrmann, D. and N{\"u}chter, A. and Dakulovic, M. and Maurovic, I. and Petrovic, I. and Osmankovic, D. and Velagic, J.}, booktitle = {Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12)}, keywords = {imported}, month = {09}, title = {{The Project ThermalMapper – Thermal 3D Mapping of Indoor Environments for Saving Energy}}, volume = 10, year = 2012 }
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  Mutual Calibration for 3D Thermal Mapping. Borrmann, D.; Afzal, H.; Elseberg, J.; Nüchter, A. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO ’12), Vol. 10. Dubrovnik, Croatia, 2012.
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  Three-dimensional digital heat distribution maps are needed to assess the energy efficiency of real estates. The availability of such maps are of great importance for reducing the ecological footprint of houses, buildings, and factories. Designing estates has reached the point, where so-called Passivhaus buildings make extensive use of the intrinsic heat from internal sources such as waste heat from lighting, white goods, and other electrical devices, but without using dedicated heaters. In our approach for creating high-precise heat distribution maps a robot is equipped with a 3D laser scanner, a thermal camera, and a color camera. Data from all the sensors are combined to model the environment precisely. This paper describes the setup of the sensors and the processing of the acquired data, including the automatic co-calibration needed to fulfill this task.

  @inproceedings{SYROCO2012_3, abstract = {Three-dimensional digital heat distribution maps are needed to assess the energy efficiency of real estates. The availability of such maps are of great importance for reducing the ecological footprint of houses, buildings, and factories. Designing estates has reached the point, where so-called Passivhaus buildings make extensive use of the intrinsic heat from internal sources such as waste heat from lighting, white goods, and other electrical devices, but without using dedicated heaters. In our approach for creating high-precise heat distribution maps a robot is equipped with a 3D laser scanner, a thermal camera, and a color camera. Data from all the sensors are combined to model the environment precisely. This paper describes the setup of the sensors and the processing of the acquired data, including the automatic co-calibration needed to fulfill this task.}, address = {Dubrovnik, Croatia}, author = {Borrmann, D. and Afzal, H. and Elseberg, J. and N{\"u}chter, A.}, booktitle = {Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12)}, keywords = {myown}, month = {09}, title = {{Mutual Calibration for 3D Thermal Mapping}}, volume = 10, year = 2012 }
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  A Toolkit for Automatic Generation of Polygonal Maps -- Las Vegas Reconstruction. Wiemann, T.; Lingemann, K.; Nüchter, A.; Hertzberg, J. In Proceedings of the 7th German Conference Robotik 2012, pp. 446–451. Munich, Germany, 2012.
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  In this paper we present a new open source software package for automatic generation of polygonal 3D maps from point cloud data for robotic purposes called "Las Vegas Reconstruction Toolkit" [11]. The implemented algorithms focus on minimizing the computational costs and optimization of the number of polygons in the generated maps. Furthermore, we present two application examples: 6D self localization and scene interpretation.

  @inproceedings{ROBOTIK2012, abstract = {In this paper we present a new open source software package for automatic generation of polygonal 3D maps from point cloud data for robotic purposes called "Las Vegas Reconstruction Toolkit" [11]. The implemented algorithms focus on minimizing the computational costs and optimization of the number of polygons in the generated maps. Furthermore, we present two application examples: 6D self localization and scene interpretation.}, address = {Munich, Germany}, author = {Wiemann, T. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J.}, booktitle = {Proceedings of the 7th German Conference Robotik 2012}, keywords = {myown}, month = {05}, pages = {446–451}, title = {A Toolkit for Automatic Generation of Polygonal Maps – Las Vegas Reconstruction}, year = 2012 }
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  Towards Reliable Object Anchoring in Highly Dynamic Traffic Scenes. Li, Ming; Li, Wei; Wang, Jian; Li, Qingquan; Nüchter, A. In Proceedings of the ICRA 2012 WORKSHOP Semantic Perception and Mapping for Knowledge-enabled Service Robotics (with interactive session and demonstrations). St. Paul, MN, USA, 2012.
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  @inproceedings{SPMK2012_WS, address = {St. Paul, MN, USA}, author = {Li, Ming and Li, Wei and Wang, Jian and Li, Qingquan and N{\"u}chter, A.}, booktitle = {Proceedings of the ICRA 2012 WORKSHOP Semantic Perception and Mapping for Knowledge-enabled Service Robotics (with interactive session and demonstrations)}, keywords = {imported}, month = {05}, title = {Towards Reliable Object Anchoring in Highly Dynamic Traffic Scenes}, year = 2012 }
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  6DOF Semi-Rigid SLAM for Mobile Scanning. Elseberg, J.; Borrmann, D.; Nüchter, A. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’12), pp. 1865–1870. Vilamoura, Algarve, Portugal, 2012.
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  The terrestrial acquisition of 3D point clouds by laser range finders has recently moved to mobile platforms. Measuring the environment while simultaneously moving the vehicle demands a high level of accuracy from positioning systems such as the IMU, GPS and odometry. We present a novel semi-rigid SLAM algorithm that corrects the global position of the vehicle at every point in time, while simultaneously improving the quality and accuracy of the entire acquired map. Using the algorithm the temporary failure of positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of our approach on a wide variety of systems and data sets.

  @inproceedings{IROS2012, abstract = {The terrestrial acquisition of 3D point clouds by laser range finders has recently moved to mobile platforms. Measuring the environment while simultaneously moving the vehicle demands a high level of accuracy from positioning systems such as the IMU, GPS and odometry. We present a novel semi-rigid SLAM algorithm that corrects the global position of the vehicle at every point in time, while simultaneously improving the quality and accuracy of the entire acquired map. Using the algorithm the temporary failure of positioning systems or the lack thereof can be compensated for. We demonstrate the capabilities of our approach on a wide variety of systems and data sets.}, address = {Vilamoura, Algarve, Portugal}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '12)}, keywords = {imported}, month = 10, pages = {1865–1870}, title = {{6DOF Semi-Rigid SLAM for Mobile Scanning}}, year = 2012 }
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  Multi-Robot Exploration and Mapping with a rotating 3D Scanner. Al khawaldah, M.; Nüchter, A. In Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO ’12), Vol. 10. Dubrovnik, Croatia, 2012.
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  This paper investigates the field of exploration and map-building with multiple cooperating mobile robots. New and efficient exploration and mapping technique is proposed by employing laser scanners. The paper also aims to extend existing exploration and mapping techniques of single robot to multi-robot to increase the exploration efficiency (i.e. to reduce the environment exploration time required). The goal of the proposed method is to have multiple mobile robots exploring a given unknown environment as fast as possible, while coordinating their actions and sharing their local maps in certain time instances. In the suggested technique, each robot is equipped with a laser scanner that is continuously rotating to scan the environment, and is employing a frontier-based exploration algorithm which is important to guide the robots during the exploration. A new factor is introduced to enhance the performance of the frontier-based exploration. This factor aims at spreading robots in the environment to reduce overlap.

  @inproceedings{SYROCO2012_1, abstract = {This paper investigates the field of exploration and map-building with multiple cooperating mobile robots. New and efficient exploration and mapping technique is proposed by employing laser scanners. The paper also aims to extend existing exploration and mapping techniques of single robot to multi-robot to increase the exploration efficiency (i.e. to reduce the environment exploration time required). The goal of the proposed method is to have multiple mobile robots exploring a given unknown environment as fast as possible, while coordinating their actions and sharing their local maps in certain time instances. In the suggested technique, each robot is equipped with a laser scanner that is continuously rotating to scan the environment, and is employing a frontier-based exploration algorithm which is important to guide the robots during the exploration. A new factor is introduced to enhance the performance of the frontier-based exploration. This factor aims at spreading robots in the environment to reduce overlap.}, address = {Dubrovnik, Croatia}, author = {Al khawaldah, M. and N{\"u}chter, A.}, booktitle = {Proceedings of the 10th International IFAC Symposium on Robot Control (SYROCO '12)}, keywords = {imported}, month = {09}, title = {{Multi-Robot Exploration and Mapping with a rotating 3D Scanner}}, volume = 10, year = 2012 }

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  The 3D Hough Transform for Plane Detection in Point Clouds -- A Review and A new Accumulator Design. Borrmann, D.; Elseberg, J.; Nüchter, A.; Lingemann, K. In Journal of 3D Research, 2(2), pp. 1–13. 2011.
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  The Hough Transform is a well-known method for detecting parameterized objects. It is the de facto standard for detecting lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Even for the 2D case high computational costs have lead to the development of numerous variations for the Hough Transform. In this article we evaluate different variants of the Hough Transform with respect to their applicability to detect planes in 3D point clouds reliably. Apart from computational costs, the main problem is the representation of the accumulator. Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. We present a novel approach to design the accumulator focusing on achieving the same size for each cell and compare it to existing designs.

  @article{3DRESEARCH2011, abstract = {The Hough Transform is a well-known method for detecting parameterized objects. It is the de facto standard for detecting lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Even for the 2D case high computational costs have lead to the development of numerous variations for the Hough Transform. In this article we evaluate different variants of the Hough Transform with respect to their applicability to detect planes in 3D point clouds reliably. Apart from computational costs, the main problem is the representation of the accumulator. Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. We present a novel approach to design the accumulator focusing on achieving the same size for each cell and compare it to existing designs.}, author = {Borrmann, D. and Elseberg, J. and N{\"u}chter, A. and Lingemann, K.}, journal = {Journal of 3D Research}, keywords = {imported}, month = {03}, number = 2, pages = {1–13}, title = {{The 3D Hough Transform for Plane Detection in Point Clouds – A Review and A new Accumulator Design}}, volume = 2, year = 2011 }
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  Localizing Google SketchUp Models in Outdoor 3D Scans. Grosan, F.; Tandrau, A.; and A. Nüchter. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT ’11). IEEE Xplore, Sarajevo, Bosnia, 2011.
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  This work introduces a novel solution for localizing objects based on search strings and freely available Google SketchUp models. To this end we automatically download and preprocess a collection of 3D models to obtain equivalent point clouds. The outdoor scan is segmented into individual objects, which are sequentially matched with the models by a variant of iterative closest points algorithm using seven degrees of freedom and resulting in a highly precise pose estimation of the object. An error function evaluates the similarity level. The approach is verified using various segmented cars and their corresponding 3D models.

  @inproceedings{ICAT2011_3, abstract = {This work introduces a novel solution for localizing objects based on search strings and freely available Google SketchUp models. To this end we automatically download and preprocess a collection of 3D models to obtain equivalent point clouds. The outdoor scan is segmented into individual objects, which are sequentially matched with the models by a variant of iterative closest points algorithm using seven degrees of freedom and resulting in a highly precise pose estimation of the object. An error function evaluates the similarity level. The approach is verified using various segmented cars and their corresponding 3D models.}, address = {Sarajevo, Bosnia}, author = {Grosan, F. and Tandrau, A. and and A. N{\"u}chter}, booktitle = {Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11)}, keywords = {myown}, month = 10, publisher = {IEEE Xplore}, title = {{Localizing Google SketchUp Models in Outdoor 3D Scans}}, year = 2011 }
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  Full Wave Analysis in 3D Laser Scans for Vegetation Detection in Urban Environments. Elseberg, J.; Borrmann, D.; Nüchter, A. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT ’11). IEEE Xplore, Sarajevo, Bosnia, 2011.
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  This paper presents a novel technique for detecting vegetation of virtually all forms in terrestrial laser scanning data of urban environments. We make use of a modern laser range finder capability to measure multiple echoes per laser pulse via Full Wave Analysis. The algorithm is able to efficiently, i.e., less than acquisition time, identify vegetation to a high degree of accuracy (more than 99 percent). We present and evaluate three alternatives to classify candidate regions as either vegetation or non-vegetation.

  @inproceedings{ICAT2011_2, abstract = {This paper presents a novel technique for detecting vegetation of virtually all forms in terrestrial laser scanning data of urban environments. We make use of a modern laser range finder capability to measure multiple echoes per laser pulse via Full Wave Analysis. The algorithm is able to efficiently, i.e., less than acquisition time, identify vegetation to a high degree of accuracy (more than 99 percent). We present and evaluate three alternatives to classify candidate regions as either vegetation or non-vegetation.}, address = {Sarajevo, Bosnia}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11)}, keywords = {imported}, month = 10, publisher = {IEEE Xplore}, title = {{Full Wave Analysis in 3D Laser Scans for Vegetation Detection in Urban Environments}}, year = 2011 }
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  SLAM à la carte - GPGPU for Globally Consistent Scan Matching. Nüchter, A.; Feyzabadi, S.; Qiu, D.; May, S. In Proceedings of the 4th European Conference on Mobile Robots (ECMR ’11). Örebro, Sweden, 2011.
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  @inproceedings{ECMR2011, address = {{\"O}rebro, Sweden}, author = {N{\"u}chter, A. and Feyzabadi, S. and Qiu, D. and May, S.}, booktitle = {Proceedings of the 4th European Conference on Mobile Robots (ECMR '11)}, keywords = {imported}, month = {09}, title = {{SLAM à la carte - GPGPU for Globally Consistent Scan Matching}}, year = 2011 }
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  Skyline-Based Registration of 3D Laser Scans. Nüchter, A.; Gutev, S.; Borrmann, D.; Elseberg, J. In Proceedings of the Joint ISPRS workshop on 3D city modelling \& applications and the 6th 3D GeoInfo (3DCMA ’11), The Chinese Academic Journal (CD ROM version) CN 11-9251/G. Wuhan, China, 2011.
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  Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.

  @inproceedings{3DCMA2011, abstract = {Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.}, address = {Wuhan, China}, author = {N{\"u}chter, A. and Gutev, S. and Borrmann, D. and Elseberg, J.}, booktitle = {Proceedings of the Joint ISPRS workshop on 3D city modelling \& applications and the 6th 3D GeoInfo (3DCMA '11), The Chinese Academic Journal (CD ROM version) CN 11-9251/G}, keywords = {imported}, month = {06}, title = {{Skyline-Based Registration of 3D Laser Scans}}, year = 2011 }
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  A Heuristic Loop Closing Technique for Large-Scale 6D SLAM. Sprickerhof, J.; Nüchter, A.; Lingemann, K.; Hertzberg, J. In AUTOMATIKA -- Journal for Control, Measurement, Electronics, Computing and Communications, Special Issue with selected papers from the 4th European Conference on Mobile Robots, 52(3). 2011.
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  This paper presents a novel heuristic for correcting scan pose estimations after loop closing in SLAM using 3D laser scans. Contrary to state of the art approaches, the built SLAM graph is sparse, and optimization is done without any iteration between the SLAM front and back end, yielding a highly efficient loop closing method. Several experiments were carried out in an urban environment and evaluated against ground truth. The results are compared to other state of the art algorithms, proving the high quality, yet achieved faster by an order of magnitude.

  @article{AUTOMATIKA2011, abstract = {This paper presents a novel heuristic for correcting scan pose estimations after loop closing in SLAM using 3D laser scans. Contrary to state of the art approaches, the built SLAM graph is sparse, and optimization is done without any iteration between the SLAM front and back end, yielding a highly efficient loop closing method. Several experiments were carried out in an urban environment and evaluated against ground truth. The results are compared to other state of the art algorithms, proving the high quality, yet achieved faster by an order of magnitude.}, author = {Sprickerhof, J. and N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, journal = {AUTOMATIKA – Journal for Control, Measurement, Electronics, Computing and Communications, Special Issue with selected papers from the 4th European Conference on Mobile Robots}, keywords = {imported}, month = 12, number = 3, title = {{A Heuristic Loop Closing Technique for Large-Scale 6D SLAM}}, volume = 52, year = 2011 }
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  Skyline-Based Registration of 3D Laser Scans. Nüchter, A.; Gutev, S.; Borrmann, D.; Elseberg, J. In Journal Geo-spatial Information Science (GSIS), Special Issue with selected papers from the 3D City Modeling and Applications Workshop, 14(2), pp. 85–90. 2011.
  • [ Abstract ]
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  Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.

  @article{GSIS2011, abstract = {Acquisition and registration of terrestrial 3D laser scans is a fundamental task in mapping and modeling of cities in three dimensions. To automate this task marker-free registration methods are required. Based on the existence of skyline features this paper proposes a novel method. The skyline features are extracted from panoramic 3D scans and encoded as strings enabling the use of string matching for merging the scans. Initial results of the proposed method in the old city center of Bremen are presented.}, author = {N{\"u}chter, A. and Gutev, S. and Borrmann, D. and Elseberg, J.}, journal = {Journal Geo-spatial Information Science (GSIS), Special Issue with selected papers from the 3D City Modeling and Applications Workshop}, keywords = {imported}, month = {05}, number = 2, pages = {85–90}, title = {{Skyline-Based Registration of 3D Laser Scans}}, volume = 14, year = 2011 }
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  Eine effiziente Octree-Datenstruktur für das Verarbeiten von grossen 3D-Punktwolken. Elseberg, J.; Borrmann, D.; Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2011, Fachhochschule Oldenburg/Ostfr./Whv., pp. 72–79. 2011.
  • [ Abstract ]
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  Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor, die es ermöglicht, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repräsentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, große Punktewolken zu inspizieren und flüssig in ihnen zu navigieren.

  @inproceedings{3DTage2011, abstract = {Dieser Beitrag stellt eine neue Implementation der Octree-Datenstruktur vor, die es ermöglicht, eine Milliarde 3D-Punkte in 8 GB Hauptspeicher exakt zu repr{\"a}sentieren und effiziente Algorithmen zu implementieren. Der Octree gibt eine Hierarchie vor, die dazu verwendet werden kann, große Punktewolken zu inspizieren und fl{\"u}ssig in ihnen zu navigieren.}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2011, Fachhochschule Oldenburg/Ostfr./Whv.}, keywords = {myown}, month = {02}, pages = {72–79}, title = {{Eine effiziente Octree-Datenstruktur f{\"u}r das Verarbeiten von grossen 3D-Punktwolken}}, year = 2011 }
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  Efficient Processing of Large 3D Point Clouds. Elseberg, J.; Borrmann, D.; Nüchter, A. In Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT ’11). IEEE Xplore, Sarajevo, Bosnia, 2011.
  • [ Abstract ]
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  Autonomous robots equipped with laser scanners acquire data at an increasingly high rate. Registration, data abstraction and visualization of this data requires the processing of a massive amount of 3D data. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling this data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for fast 3D scan matching and shape detection algorithms. We evaluate our approach using typical data acquired by mobile scanning platforms.

  @inproceedings{ICAT2011_1, abstract = {Autonomous robots equipped with laser scanners acquire data at an increasingly high rate. Registration, data abstraction and visualization of this data requires the processing of a massive amount of 3D data. The increasing sampling rates make it easy to acquire Billions of spatial data points. This paper presents algorithms and data structures for handling this data. We propose an efficient octree to store and compress 3D data without loss of precision. We demonstrate its usage for fast 3D scan matching and shape detection algorithms. We evaluate our approach using typical data acquired by mobile scanning platforms.}, address = {Sarajevo, Bosnia}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A.}, booktitle = {Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11)}, keywords = {myown}, month = 10, publisher = {IEEE Xplore}, title = {{Efficient Processing of Large 3D Point Clouds}}, year = 2011 }

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  3D-Roboterkartenbau in Osnabrück. Hertzberg, J.; Lingemann, K.; Lörken, C.; Nüchter, A.; Stiene, S.; Wiemann, T. In KI -- Künstliche Intelligenz: Themenschwerpunk Simultaneous Localization and Mapping (SLAM), 24(3), pp. 245–248. 2010.
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  Seit Herbst 2004 existiert die Arbeitsgruppe „Wissensbasierte Systeme“ am Institut für Informatik der Universität Osnabrück. Ein Langfristziel der Arbeitsgruppe besteht darin, Schlussfolgerungs- und Planungsverfahren der KI für den Einsatz online und onboard auf mobilen Robotern einsetzbar zu machen. Ein daraus abgeleitetes Arbeitsthema ist der Bau von semantischen Roboterkarten basierend auf 3D-Laserscans bei 6-dimensionalen Scanposen. Wir geben einen Überblick über die wichtigsten Ergebnisse dazu und über unsere Perspektive dieses Themas für die Zukunft.

  @article{KI2009, abstract = {Seit Herbst 2004 existiert die Arbeitsgruppe „Wissensbasierte Systeme“ am Institut für Informatik der Universität Osnabrück. Ein Langfristziel der Arbeitsgruppe besteht darin, Schlussfolgerungs- und Planungsverfahren der KI für den Einsatz online und onboard auf mobilen Robotern einsetzbar zu machen. Ein daraus abgeleitetes Arbeitsthema ist der Bau von semantischen Roboterkarten basierend auf 3D-Laserscans bei 6-dimensionalen Scanposen. Wir geben einen Überblick über die wichtigsten Ergebnisse dazu und über unsere Perspektive dieses Themas für die Zukunft.}, author = {Hertzberg, J. and Lingemann, K. and L{\"o}rken, C. and N{\"u}chter, A. and Stiene, S. and Wiemann, T.}, journal = {KI – K{\"u}nstliche Intelligenz: Themenschwerpunk Simultaneous Localization and Mapping (SLAM)}, keywords = {myown}, month = {09}, number = 3, pages = {245–248}, title = {{3D-Roboterkartenbau in Osnabr{\"u}ck}}, volume = 24, year = 2010 }
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  Lifelong 3D Mapping -- Monitoring with a 3D Scanner. Borrmann, D.; Elseberg, J.; Raunyar, S. S.; Nüchter, A. In Proceedings of the IROS Workshop on Robotics for Environmental Monitoring (WREM ’10). Taipei, Taiwan, 2010.
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  Geodesy and surveying are the sciences for monitoring the earth. In recent years traditional surveying equipment has been pushed aside by the emerging technology of laser scanners, that automate the precise measurement of points in the environment. A further step of automation is achieved by operating the surveying equipment automatically and the usage of robotic mapping. Thus, robotic mapping will become a key component in monitoring and surveillance tasks. This paper evaluates a 3D laser scanner from surveying for its usage in robotic monitoring tasks. We examine how seasonal changes and weather conditions impact the data of the 3D scanner and how to deal with these changes. For this analysis 3D scans of various predetermined locations on the campus of the Jacobs University Bremen were taken on a weekly basis over a period of 13 weeks using the RIEGL VZ-400 3D laser range finder. The scans have been registered by means of conventional surveying markers, SIFT features and using our point cloud based 6D SLAM framework. An analysis of the changes in the environment over the course of the scanning period and an evaluation of the matching results complete the analysis.

  @inproceedings{WREM2010, abstract = {Geodesy and surveying are the sciences for monitoring the earth. In recent years traditional surveying equipment has been pushed aside by the emerging technology of laser scanners, that automate the precise measurement of points in the environment. A further step of automation is achieved by operating the surveying equipment automatically and the usage of robotic mapping. Thus, robotic mapping will become a key component in monitoring and surveillance tasks. This paper evaluates a 3D laser scanner from surveying for its usage in robotic monitoring tasks. We examine how seasonal changes and weather conditions impact the data of the 3D scanner and how to deal with these changes. For this analysis 3D scans of various predetermined locations on the campus of the Jacobs University Bremen were taken on a weekly basis over a period of 13 weeks using the RIEGL VZ-400 3D laser range finder. The scans have been registered by means of conventional surveying markers, SIFT features and using our point cloud based 6D SLAM framework. An analysis of the changes in the environment over the course of the scanning period and an evaluation of the matching results complete the analysis.}, address = {Taipei, Taiwan}, author = {Borrmann, D. and Elseberg, J. and Raunyar, S. S. and N{\"u}chter, A.}, booktitle = {Proceedings of the IROS Workshop on Robotics for Environmental Monitoring (WREM '10)}, keywords = {imported}, month = 10, title = {Lifelong 3D Mapping – Monitoring with a 3D Scanner}, year = 2010 }
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  Verbesserte Kartenqualität durch Thin Plate Splines und Hough-Transformation. Elseberg, J.; Nüchter, A.; Borrmann, D.; Lingemann, K. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2010, Fachhochschule Oldenburg/Ostfr./Whv., pp. 134–141. 2010.
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  Laserscanner sind präzise Messgeräte zur Ermittlung von Distanzwerten. Dennoch weist eine jede mit einem Laserscanner akquirierte Punktwolke Fehler auf, die auch durch Kalibrierung nicht vollständig verhindert werden können. Neben Sensorrauschen kommt es auch zu systematischen Fehlern. Die meisten künstlich geschaffenen Umgebungen bestehen aus einer großen Anzahl ebener Flächen, die helfen können, die Qualität von Laserscan-Karten zu verbessern. Dieser Aufsatz stellt Methoden vor, die unter Zuhilfenahme von ebenen Umgebungsstrukturen die Fehler in den Laserscans durch nicht-rigide Verformungen verringern

  @inproceedings{3DTage2010, abstract = {Laserscanner sind präzise Messgeräte zur Ermittlung von Distanzwerten. Dennoch weist eine jede mit einem Laserscanner akquirierte Punktwolke Fehler auf, die auch durch Kalibrierung nicht vollständig verhindert werden können. Neben Sensorrauschen kommt es auch zu systematischen Fehlern. Die meisten künstlich geschaffenen Umgebungen bestehen aus einer großen Anzahl ebener Flächen, die helfen können, die Qualität von Laserscan-Karten zu verbessern. Dieser Aufsatz stellt Methoden vor, die unter Zuhilfenahme von ebenen Umgebungsstrukturen die Fehler in den Laserscans durch nicht-rigide Verformungen verringern}, author = {Elseberg, J. and N{\"u}chter, A. and Borrmann, D. and Lingemann, K.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2010, Fachhochschule Oldenburg/Ostfr./Whv.}, keywords = {myown}, month = {01}, pages = {134–141}, title = {{Verbesserte Kartenqualit{\"a}t durch Thin Plate Splines und Hough-Transformation}}, year = 2010 }
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  Evaluation of the Robustness of Planar-Patches based 3D-Registration using Marker-based Ground-Truth in an Outdoor Urban Scenario. Pathak, K.; Borrmann, D.; Elseberg, J.; Vaskevicius, N.; Birk, A.; Nüchter, A. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’10), pp. 5725–5730. Taipei, Taiwan, 2010.
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  The recently introduced Minimum Uncertainty Maximum Consensus (MUMC) algorithm for 3D scene registration using planar-patches is tested in a large outdoor urban setting without any prior motion estimate whatsoever. With the aid of a new overlap metric based on unmatched patches, the algorithm is shown to work successfully in most cases. The absolute accuracy of its computed result is corroborated for the first time by ground-truth obtained using reflective markers. There were a couple of unsuccessful scan-pairs. These are analyzed for the reason of failure by formulating two kinds of overlap metrics: one based on the actual overlapping surface-area and another based on the extent of agreement of range-image pixels. We conclude that neither metric in isolation is able to predict all failures, but that both taken together are able to predict the difficulty level of a scan-pair vis-à-vis registration by MUMC.

  @inproceedings{IROS2010_2, abstract = {The recently introduced Minimum Uncertainty Maximum Consensus (MUMC) algorithm for 3D scene registration using planar-patches is tested in a large outdoor urban setting without any prior motion estimate whatsoever. With the aid of a new overlap metric based on unmatched patches, the algorithm is shown to work successfully in most cases. The absolute accuracy of its computed result is corroborated for the first time by ground-truth obtained using reflective markers. There were a couple of unsuccessful scan-pairs. These are analyzed for the reason of failure by formulating two kinds of overlap metrics: one based on the actual overlapping surface-area and another based on the extent of agreement of range-image pixels. We conclude that neither metric in isolation is able to predict all failures, but that both taken together are able to predict the difficulty level of a scan-pair vis-à-vis registration by MUMC.}, address = {Taipei, Taiwan}, author = {Pathak, K. and Borrmann, D. and Elseberg, J. and Vaskevicius, N. and Birk, A. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10)}, keywords = {imported}, month = 10, pages = {5725–5730}, title = {{Evaluation of the Robustness of Planar-Patches based 3D-Registration using Marker-based Ground-Truth in an Outdoor Urban Scenario}}, year = 2010 }
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  Study of Parameterizations for the Rigid Body Transformations of The Scan Registration Problem. Nüchter, A.; Elseberg, J.; Schneider, P.; Paulus, D. In Journal Computer Vision and Image Understanding (CVIU), 114(8), pp. 963–980. 2010.
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  The iterative closest point (ICP) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering n-scans in a global and simultaneous fashion, such that the registration of the nth scan influences all previous registrations in one step.

  @article{CVIU2010, abstract = {The iterative closest point (ICP) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. Four closed-form solution methods are known for minimizing this function. This paper presents novel linear solutions to the scan registration problem, i.e., to the problem of putting and aligning 3D scans in a common coordinate system. We extend the methods for registering n-scans in a global and simultaneous fashion, such that the registration of the nth scan influences all previous registrations in one step.}, author = {N{\"u}chter, A. and Elseberg, J. and Schneider, P. and Paulus, D.}, journal = {Journal Computer Vision and Image Understanding (CVIU)}, keywords = {imported}, month = {08}, number = 8, pages = {963–980}, title = {{Study of Parameterizations for the Rigid Body Transformations of The Scan Registration Problem}}, volume = 114, year = 2010 }
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  Automatic Construction of Polygonal Maps From Point Cloud Data. Wiemann, T.; Nüchter, A.; Lingemann, K.; Stiene, S.; Hertzberg, J. In Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR ’10). Bremen, Germany, 2010.
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  This paper presents a novel approach to create polygonal maps from 3D point cloud data. The gained map is augmented with an interpretation of the scene. Our procedure produces accurate maps of indoor environments fast and reliably. These maps are successfully used by different robots with varying sensor configurations for reliable self localization.

  @inproceedings{SSRR2010, abstract = {This paper presents a novel approach to create polygonal maps from 3D point cloud data. The gained map is augmented with an interpretation of the scene. Our procedure produces accurate maps of indoor environments fast and reliably. These maps are successfully used by different robots with varying sensor configurations for reliable self localization.}, address = {Bremen, Germany}, author = {Wiemann, T. and N{\"u}chter, A. and Lingemann, K. and Stiene, S. and Hertzberg, J.}, booktitle = {Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR '10)}, keywords = {myown}, month = {07}, title = {{Automatic Construction of Polygonal Maps From Point Cloud Data}}, year = 2010 }
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  Linearization of Rotations for Globally Consistent $n$-Scan Matching. Nüchter, A.; Elseberg, J.; Schneider, P.; Paulus, D. In Proceedings of the IEEE International Conference Robotics and Automation (ICRA ’10), pp. 1373–1379. Anchorage, Alaska, USA, 2010.
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  The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. While four closed-form solution methods are known for minimizing this function, linearization seems necessary for solving the global scan registration problem. This paper presents such linear solutions for registering n-scans in a global and simultaneous fashion. It studies parameterizations for the rigid body transformations of the n-scan registration problem.

  @inproceedings{ICRA2010, abstract = {The ICP (Iterative Closest Point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of the algorithm is the minimization of an error function that takes point correspondences into account. While four closed-form solution methods are known for minimizing this function, linearization seems necessary for solving the global scan registration problem. This paper presents such linear solutions for registering n-scans in a global and simultaneous fashion. It studies parameterizations for the rigid body transformations of the n-scan registration problem.}, address = {Anchorage, Alaska, USA}, author = {N{\"u}chter, A. and Elseberg, J. and Schneider, P. and Paulus, D.}, booktitle = {Proceedings of the IEEE International Conference Robotics and Automation (ICRA '10)}, keywords = {imported}, month = {05}, pages = {1373–1379}, title = {{Linearization of Rotations for Globally Consistent $n$-Scan Matching}}, year = 2010 }
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  Exploration Strategies for a Robot with a Continously Rotating 3D Scanner. Digor, E.; Birk, A.; Nüchter, A. In Proceedings of the Second International Conference on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR ’10), Vol. 6472 of Lecture Notes in Computer Science, pp. 374–386. Darmstadt, Germany, 2010.
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  To benchmark the efficiency of exploration strategies one has to use robot simulators. In an exploration task, the robot faces an unknown environment. Of course one could test the algorithm in different real-world scenarios, but a competitive strategy must have good performance in any environment that can be systematically constructed inside a simulator. This paper presents an evaluation of exploration strategies we developed for a specific sensor. A continously rotating 3D laser scanner that scans only into one direction at a time moves through the environment sampling the surrounding. Our evaluation framework features an efficient scanning and robot simulator for kinematic feasible trajectories. We will show that shorter trajectories do not necessarily imply quicker exploration. A simple simulator framework is sufficient for evaluating these properties of path planning algorithms.

  @inproceedings{SIMPAR2010, abstract = {To benchmark the efficiency of exploration strategies one has to use robot simulators. In an exploration task, the robot faces an unknown environment. Of course one could test the algorithm in different real-world scenarios, but a competitive strategy must have good performance in any environment that can be systematically constructed inside a simulator. This paper presents an evaluation of exploration strategies we developed for a specific sensor. A continously rotating 3D laser scanner that scans only into one direction at a time moves through the environment sampling the surrounding. Our evaluation framework features an efficient scanning and robot simulator for kinematic feasible trajectories. We will show that shorter trajectories do not necessarily imply quicker exploration. A simple simulator framework is sufficient for evaluating these properties of path planning algorithms.}, address = {Darmstadt, Germany}, author = {Digor, E. and Birk, A. and N{\"u}chter, A.}, booktitle = {Proceedings of the Second International Conference on Simulation, Modeling and Programming for Autonomous Robots (SIMPAR '10)}, keywords = {myown}, month = 11, pages = {374–386}, series = {Lecture Notes in Computer Science}, title = {Exploration Strategies for a Robot with a Continously Rotating 3D Scanner}, volume = 6472, year = 2010 }
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  A Data Structure for the 3D Hough Transform for Plane Detection. Borrmann, D.; Elseberg, J.; Lingemann, K.; Nüchter, A. In Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV ’10). Lecce, Italy, 2010.
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  The Hough Transform is a well-known method for detecting parametrized objects. It is the de facto standard for the detection of lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Apart from computational costs, the main problem is the representation of the accumulator: Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. In this paper we present a novel approach to design the accumulator focusing on achieving the same size for each cell. The proposed accumulator is compared to previously known designs.

  @inproceedings{IAV2010_1, abstract = {The Hough Transform is a well-known method for detecting parametrized objects. It is the de facto standard for the detection of lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Apart from computational costs, the main problem is the representation of the accumulator: Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. In this paper we present a novel approach to design the accumulator focusing on achieving the same size for each cell. The proposed accumulator is compared to previously known designs.}, address = {Lecce, Italy}, author = {Borrmann, D. and Elseberg, J. and Lingemann, K. and N{\"u}chter, A.}, booktitle = {Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '10)}, keywords = {myown}, month = {09}, title = {{A Data Structure for the 3D Hough Transform for Plane Detection}}, year = 2010 }
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  Non-Rigid Registration and Rectification of 3D Laser Scans. Elseberg, J.; Borrmann, D.; Nüchter, A.; Lingemann, K. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’10), pp. 1546–1552. Taipei, Taiwan, 2010.
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  Three dimensional point clouds acquired by range scanners often do not represent the environment precisely due to noise and errors in the acquisition process. These latter systematical errors manifest as deformations of different kinds in the 3D range image. This paper presents a novel approach to correct deformations by an analysis of the structures present in the environment and correcting them by non-rigid transformations. The resulting algorithms are used for creating high-accuracy 3D indoor maps.

  @inproceedings{IROS2010_1, abstract = {Three dimensional point clouds acquired by range scanners often do not represent the environment precisely due to noise and errors in the acquisition process. These latter systematical errors manifest as deformations of different kinds in the 3D range image. This paper presents a novel approach to correct deformations by an analysis of the structures present in the environment and correcting them by non-rigid transformations. The resulting algorithms are used for creating high-accuracy 3D indoor maps.}, address = {Taipei, Taiwan}, author = {Elseberg, J. and Borrmann, D. and N{\"u}chter, A. and Lingemann, K.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '10)}, keywords = {myown}, month = 10, pages = {1546–1552}, title = {{Non-Rigid Registration and Rectification of 3D Laser Scans}}, year = 2010 }
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  Towards Real Time Robot 6D Localization in a Polygonal Indoor Map Based on 3D ToF Camera Data. Wülfing, J.; Hertzberg, J.; Lingemann, K.; Nüchter, A.; Wiemann, T.; Stiene, S. In Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV ’10). Lecce, Italy, 2010.
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  This paper reports a method and results for solving the following problem: Given a 3D polygonal indoor map and a mobile robot equipped with a 3D time of flight (ToF) camera, localize at frame rate the 6D robot pose with respect to the map. To solve the problem, the polygonal map is represented for efficient usage as a solid-leaf BSP tree; at each control cycle, the 6D pose change is estimated a priori from odometry or IMU, the expected ToF camera view at the prior pose sampled from the BSP tree, and the pose change estimation corrected a posteriori by fast ICP matching of the expected and the measured ToF image. Our experiments indicate that, first, the method is in fact real-time capable; second, the 6D pose is tracked reliably in a correct map under regular sensor conditions; and third, the tracking can recover from some faults induced by local map inaccuracies and transient or local sensing errors.

  @inproceedings{IAV2010_2, abstract = {This paper reports a method and results for solving the following problem: Given a 3D polygonal indoor map and a mobile robot equipped with a 3D time of flight (ToF) camera, localize at frame rate the 6D robot pose with respect to the map. To solve the problem, the polygonal map is represented for efficient usage as a solid-leaf BSP tree; at each control cycle, the 6D pose change is estimated a priori from odometry or IMU, the expected ToF camera view at the prior pose sampled from the BSP tree, and the pose change estimation corrected a posteriori by fast ICP matching of the expected and the measured ToF image. Our experiments indicate that, first, the method is in fact real-time capable; second, the 6D pose is tracked reliably in a correct map under regular sensor conditions; and third, the tracking can recover from some faults induced by local map inaccuracies and transient or local sensing errors.}, address = {Lecce, Italy}, author = {W{\"u}lfing, J. and Hertzberg, J. and Lingemann, K. and N{\"u}chter, A. and Wiemann, T. and Stiene, S.}, booktitle = {Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '10)}, keywords = {myown}, month = {09}, title = {{Towards Real Time Robot 6D Localization in a Polygonal Indoor Map Based on 3D ToF Camera Data}}, year = 2010 }

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  3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom. Nüchter, A. In of Springer Tracts in Advanced Robotics. Springer, 2009.
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  @book{3DMAPPING, author = {N{\"u}chter, A.}, keywords = {imported}, month = {02}, number = 52, publisher = {Springer}, series = {Springer Tracts in Advanced Robotics}, title = {3D Robotic Mapping: The Simultaneous Localization and Mapping Problem with Six Degrees of Freedom}, year = 2009 }
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  Automatic Appearance-Based Loop Detection from 3D Laser Data Using the Normal Distributions Transform. Magnusson, M.; Andreasson, H.; Nüchter, A.; Lilienthal, A. J. In Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping, 26(11--12), pp. 934–965. 2009.
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  We propose a new approach to appearance-based loop detection for mobile robots, using three-dimensional (3D) laser scans. Loop detection is an important problem in the simultaneous localization and mapping (SLAM) domain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat-floor assumption, two-dimensional laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3D rotations. We present a compact representation of 3D point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). A low false-positive rate is very important because wrong data association could have disastrous consequences in a SLAM algorithm. Our approach uses only the appearance of 3D point clouds to detect loops and requires no pose information. We exploit the normal distributions transform surface representation to create feature histograms based on surface orientation and smoothness. The surface shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. We also propose to use expectation maximization to fit a gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from nonoverlapping ones. We discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. Furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false-positive rates in environments with different characteristics.

  @article{JFR2009_2, abstract = {We propose a new approach to appearance-based loop detection for mobile robots, using three-dimensional (3D) laser scans. Loop detection is an important problem in the simultaneous localization and mapping (SLAM) domain, and, because it can be seen as the problem of recognizing previously visited places, it is an example of the data association problem. Without a flat-floor assumption, two-dimensional laser-based approaches are bound to fail in many cases. Two of the problems with 3D approaches that we address in this paper are how to handle the greatly increased amount of data and how to efficiently obtain invariance to 3D rotations. We present a compact representation of 3D point clouds that is still discriminative enough to detect loop closures without false positives (i.e., detecting loop closure where there is none). A low false-positive rate is very important because wrong data association could have disastrous consequences in a SLAM algorithm. Our approach uses only the appearance of 3D point clouds to detect loops and requires no pose information. We exploit the normal distributions transform surface representation to create feature histograms based on surface orientation and smoothness. The surface shape histograms compress the input data by two to three orders of magnitude. Because of the high compression rate, the histograms can be matched efficiently to compare the appearance of two scans. Rotation invariance is achieved by aligning scans with respect to dominant surface orientations. We also propose to use expectation maximization to fit a gamma mixture model to the output similarity measures in order to automatically determine the threshold that separates scans at loop closures from nonoverlapping ones. We discuss the problem of determining ground truth in the context of loop detection and the difficulties in comparing the results of the few available methods based on range information. Furthermore, we present quantitative performance evaluations using three real-world data sets, one of which is highly self-similar, showing that the proposed method achieves high recall rates (percentage of correctly identified loop closures) at low false-positive rates in environments with different characteristics.}, author = {Magnusson, M. and Andreasson, H. and N{\"u}chter, A. and Lilienthal, A. J.}, journal = {Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping}, keywords = {imported}, number = {11–12}, pages = {934–965}, title = {{Automatic Appearance-Based Loop Detection from 3D Laser Data Using the Normal Distributions Transform}}, volume = 26, year = 2009 }
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  3D Mapping with Time-of-Flight Cameras. May, S.; Dröschel, D.; Holz, D.; Fuchs, S.; Malis, E.; Nüchter, A.; Hertzberg, J. In Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping, 26(11--12), pp. 892–914. 2009.
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  This article investigates the use of time-of-flight (ToF) cameras in mapping tasks for autonomous mobile robots, in particular in simultaneous localization and mapping (SLAM) tasks. Although ToF cameras are in principle an attractive type of sensor for three-dimensional (3D) mapping owing to their high rate of frames of 3D data, two features make them difficult as mapping sensors, namely, their restricted field of view and influences on the quality of range measurements by high dynamics in object reflectivity; in addition, currently available models suffer from poor data quality in a number of aspects. The paper first summarizes calibration and filtering approaches for improving the accuracy, precision, and robustness of ToF cameras independent of their intended usage. Then, several ego motion estimation approaches are applied or adapted, respectively, in order to provide a performance benchmark for registering ToF camera data. As a part of this, an extension to the iterative closest point algorithm has been developed that increases the robustness under restricted field of view and under larger displacements. Using an indoor environment, the paper provides results from SLAM experiments using these approaches in comparison. It turns out that the application of ToF cameras is feasible to SLAM tasks, although this type of sensor has a complex error characteristic.

  @article{JFR2009_1, abstract = {This article investigates the use of time-of-flight (ToF) cameras in mapping tasks for autonomous mobile robots, in particular in simultaneous localization and mapping (SLAM) tasks. Although ToF cameras are in principle an attractive type of sensor for three-dimensional (3D) mapping owing to their high rate of frames of 3D data, two features make them difficult as mapping sensors, namely, their restricted field of view and influences on the quality of range measurements by high dynamics in object reflectivity; in addition, currently available models suffer from poor data quality in a number of aspects. The paper first summarizes calibration and filtering approaches for improving the accuracy, precision, and robustness of ToF cameras independent of their intended usage. Then, several ego motion estimation approaches are applied or adapted, respectively, in order to provide a performance benchmark for registering ToF camera data. As a part of this, an extension to the iterative closest point algorithm has been developed that increases the robustness under restricted field of view and under larger displacements. Using an indoor environment, the paper provides results from SLAM experiments using these approaches in comparison. It turns out that the application of ToF cameras is feasible to SLAM tasks, although this type of sensor has a complex error characteristic.}, author = {May, S. and Dr{\"o}schel, D. and Holz, D. and Fuchs, S. and Malis, E. and N{\"u}chter, A. and Hertzberg, J.}, journal = {Journal of Field Robotics (JFR), Special Issue on Three-Dimensional Mapping}, keywords = {imported}, number = {11–12}, pages = {892–914}, title = {{3D Mapping with Time-of-Flight Cameras}}, volume = 26, year = 2009 }
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  Attentive Classification. Frintrop, S.; Nüchter, A.; Pervölz, K.; Surmann, H.; Mitri, S.; Hertzberg, J. In International Journal of Applied Artificial Intelligence in Engineering Systems, 1(1). 2009.
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  In this paper, we present a two-step approach for object recognition based on principles of human perception: Attentive Classification. First, regions of interest are detected by a biologically motivated attention system. Second, these regions are analyzed by a fast classifier based on the Adaboost learning technique. Thus, the classification effort is restricted to a small data subset. The approach has two advantages over normal classification: First, the system becomes considerably faster, which is an important factor for real-time systems. Second, since the attention system is able to make use of top-down target-information, the combination of the systems yields a significant reduction of false detections for objects which are usually difficult to discriminate from the surrounding. We show the performance of the system in several experiments in robotic scenarios. The presented attentive classification system represents an important step towards effective general object recognition which is fast, robust and flexibly adaptable to a current task.

  @article{IJAAIES2009, abstract = {In this paper, we present a two-step approach for object recognition based on principles of human perception: Attentive Classification. First, regions of interest are detected by a biologically motivated attention system. Second, these regions are analyzed by a fast classifier based on the Adaboost learning technique. Thus, the classification effort is restricted to a small data subset. The approach has two advantages over normal classification: First, the system becomes considerably faster, which is an important factor for real-time systems. Second, since the attention system is able to make use of top-down target-information, the combination of the systems yields a significant reduction of false detections for objects which are usually difficult to discriminate from the surrounding. We show the performance of the system in several experiments in robotic scenarios. The presented attentive classification system represents an important step towards effective general object recognition which is fast, robust and flexibly adaptable to a current task.}, author = {Frintrop, S. and N{\"u}chter, A. and Perv{\"o}lz, K. and Surmann, H. and Mitri, S. and Hertzberg, J.}, journal = {International Journal of Applied Artificial Intelligence in Engineering Systems}, keywords = {imported}, number = 1, title = {Attentive Classification}, volume = 1, year = 2009 }
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  Appearance-Based Place Recognition from 3D Laser Data Using the Normal Distributions Transform. Magnusson, M.; Andreasson, H.; Nüchter, A.; Lilienthal, A. J. In Proceedings of the IEEE International Conference Robotics and Automation (ICRA ’09), pp. 23–28. Kobe, Japan, 2009.
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  To advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. However, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experiences obtained during the original development process. This paper presents the results of a field experiment, carried out by two research groups that are leading in the field of 3D robotic mapping. The iterative closest points algorithm (ICP) is compared to the normal distributions transform (NDT). We also present an improved version of NDT with a substantially larger valley of convergence than previously published versions.

  @inproceedings{ICRA2009_1, abstract = {To advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. However, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experiences obtained during the original development process. This paper presents the results of a field experiment, carried out by two research groups that are leading in the field of 3D robotic mapping. The iterative closest points algorithm (ICP) is compared to the normal distributions transform (NDT). We also present an improved version of NDT with a substantially larger valley of convergence than previously published versions.}, address = {Kobe, Japan}, author = {Magnusson, M. and Andreasson, H. and N{\"u}chter, A. and Lilienthal, A. J.}, booktitle = {Proceedings of the IEEE International Conference Robotics and Automation (ICRA '09)}, keywords = {imported}, month = {05}, pages = {23–28}, title = {{Appearance-Based Place Recognition from 3D Laser Data Using the Normal Distributions Transform}}, year = 2009 }
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  An Explicit Loop Closing Technique for 6D SLAM. Sprickerhof, J.; Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings of the 4th European Conference on Mobile Robots (ECMR ’09). Mlini/Dubrovnic, Croatia, 2009.
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  Simultaneous Localization and Mapping (SLAM) is the problem of building a map of an unknown environment by a mobile robot while at the same time navigating the environment, using the unfinished map. For SLAM, two tasks have to be solved: First reliable feature extraction and data association, second the optimal estimation of poses and features. These two parts are often referred to as SLAM frontend and backend. Algorithms that solve SLAM by using laser scans commonly rely on matching closest points in the frontend part. Then the SLAM front- and backend have to be iterated to ensure that the map converges. This paper presents a novel approach for solving SLAM using 3D laser range scans. We aim at avoiding the iteration between the SLAM front- and backend and propose a novel explicit loop closing heuristic (ELCH). It dissociates the last scan of a sequence of acquired scans, reassociates it to the map, built so far by scan registration, and distributes the difference in the pose error over the SLAM graph. We describe ELCH in the context of SLAM with 3D scans considering 6 DoF. The performance is evaluated using ground truth data of an urban environment.

  @inproceedings{ECMR2009, abstract = {Simultaneous Localization and Mapping (SLAM) is the problem of building a map of an unknown environment by a mobile robot while at the same time navigating the environment, using the unfinished map. For SLAM, two tasks have to be solved: First reliable feature extraction and data association, second the optimal estimation of poses and features. These two parts are often referred to as SLAM frontend and backend. Algorithms that solve SLAM by using laser scans commonly rely on matching closest points in the frontend part. Then the SLAM front- and backend have to be iterated to ensure that the map converges. This paper presents a novel approach for solving SLAM using 3D laser range scans. We aim at avoiding the iteration between the SLAM front- and backend and propose a novel explicit loop closing heuristic (ELCH). It dissociates the last scan of a sequence of acquired scans, reassociates it to the map, built so far by scan registration, and distributes the difference in the pose error over the SLAM graph. We describe ELCH in the context of SLAM with 3D scans considering 6 DoF. The performance is evaluated using ground truth data of an urban environment.}, address = {Mlini/Dubrovnic, Croatia}, author = {Sprickerhof, J. and N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the 4th European Conference on Mobile Robots (ECMR '09)}, keywords = {imported}, month = {09}, title = {{An Explicit Loop Closing Technique for 6D SLAM}}, year = 2009 }
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  Robust 3D-Mapping with Time-of-Flight Cameras. May, S.; Dröschel, D.; Holz, D.; Fuchs, S.; Nüchter, A. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’09), pp. 1673–1678. St. Louis, MO, USA, 2009.
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  Time-of-flight cameras constitute a smart and fast technology for 3D perception but lack in measurement precision and robustness. The authors present a comprehensive approach for 3D environment mapping based on this technology. Imprecision of depth measurements are properly handled by calibration and application of several filters. Robust registration is performed by a novel extension to the Iterative Closest Point algorithm. Remaining registration errors are reduced by global relaxation after loop-closure and surface smoothing. A laboratory ground truth evaluation is provided as well as 3D mapping experiments in a larger indoor environment.

  @inproceedings{IROS2009, abstract = {Time-of-flight cameras constitute a smart and fast technology for 3D perception but lack in measurement precision and robustness. The authors present a comprehensive approach for 3D environment mapping based on this technology. Imprecision of depth measurements are properly handled by calibration and application of several filters. Robust registration is performed by a novel extension to the Iterative Closest Point algorithm. Remaining registration errors are reduced by global relaxation after loop-closure and surface smoothing. A laboratory ground truth evaluation is provided as well as 3D mapping experiments in a larger indoor environment.}, address = {St. Louis, MO, USA}, author = {May, S. and Dr{\"o}schel, D. and Holz, D. and Fuchs, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '09)}, keywords = {imported}, month = 10, pages = {1673–1678}, title = {{Robust 3D-Mapping with Time-of-Flight Cameras}}, year = 2009 }
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  6D SLAM mit Global Konsistentem Scanmatching. Nüchter, A. In Terrestrisches Laserscanning (TLS 2009) Beiträge zum DVW-Seminar am 18. und 19. November in Fulda, pp. 69–92. Fulda, Germany, 2009.
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  Terrestrisches Laserscanning (TLS) hat die in den letzten Jahren die Vermessungstechnik revolutioniert. Durch die Entwicklung des kinematischen terrestrischen Laserscannings (k-TLS) oder Mobile Mapping, das die Aufnahme von geometrische Umgebungsinformation von einer bewegten Plattform aus erlaubt, wurde ein wesentlicher Schritt zur weiteren Automatisierung in der Vermessungstechnik getan. Leider ist k-TLS nicht überall einsetzbar, da neben den Daten des Laserscanners hochgenaue Informationen über die Pose (Position und Orientierung) der mobilen Plattform vorliegen müssen. Technischer Fortschritt erlaubt den Bau von autonomen Robotersystemen, die mit 3D-Laserscannern ausgestattet sind und es besteht Potential für weitere Automatisierung. Dazu muss das Problem der gleichzeitigen Lokalisation und Kartierung gelöst werden. Dieses klassische Robotikproblem ist ein Henne-und-Ei-Problem: Mit genauster Kenntnis der Position des mobilen Roboters lassen sich korrekte Karten erzeugen. Mit Hilfe von Karten können sich Roboter sehr genau lokalisieren. Beides gleichzeitig durchzuführen stellt neue hohe Anforderungen an die Algorithmen, die Scannerdaten verarbeiten.

  @inproceedings{TLS2009, abstract = {Terrestrisches Laserscanning (TLS) hat die in den letzten Jahren die Vermessungstechnik revolutioniert. Durch die Entwicklung des kinematischen terrestrischen Laserscannings (k-TLS) oder Mobile Mapping, das die Aufnahme von geometrische Umgebungsinformation von einer bewegten Plattform aus erlaubt, wurde ein wesentlicher Schritt zur weiteren Automatisierung in der Vermessungstechnik getan. Leider ist k-TLS nicht überall einsetzbar, da neben den Daten des Laserscanners hochgenaue Informationen über die Pose (Position und Orientierung) der mobilen Plattform vorliegen müssen. Technischer Fortschritt erlaubt den Bau von autonomen Robotersystemen, die mit 3D-Laserscannern ausgestattet sind und es besteht Potential für weitere Automatisierung. Dazu muss das Problem der gleichzeitigen Lokalisation und Kartierung gelöst werden. Dieses klassische Robotikproblem ist ein Henne-und-Ei-Problem: Mit genauster Kenntnis der Position des mobilen Roboters lassen sich korrekte Karten erzeugen. Mit Hilfe von Karten können sich Roboter sehr genau lokalisieren. Beides gleichzeitig durchzuführen stellt neue hohe Anforderungen an die Algorithmen, die Scannerdaten verarbeiten.}, address = {Fulda, Germany}, author = {N{\"u}chter, A.}, booktitle = {Terrestrisches Laserscanning (TLS 2009) Beitr{\"a}ge zum DVW-Seminar am 18. und 19. November in Fulda}, keywords = {imported}, month = 11, pages = {69–92}, title = {{6D SLAM mit Global Konsistentem Scanmatching}}, year = 2009 }
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  Evaluation of 3D Registration Reliability and Speed -- A Comparison of ICP and NDT. Magnusson, M.; A. Nüchter, C. Lörken; Lilienthal, A. J.; Hertzberg, J. In Proceedings of the IEEE International Conference Robotics and Automation (ICRA ’09), pp. 3907–3912. Kobe, Japan, 2009.
  • [ Abstract ]
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  To advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. However, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experience obtained during the original development process. This paper presents a thorough comparison of 3D scan registration algorithms based on a 3D mapping field experiment, carried out by two research groups that are leading in the field of 3D robotic mapping. The iterative closest points algorithm (ICP) is compared to the normal distributions transform (NDT). We also present an improved version of NDT with a substantially larger valley of convergence than previously published versions.

  @inproceedings{ICRA2009_2, abstract = {To advance robotic science it is important to perform experiments that can be replicated by other researchers to compare different methods. However, these comparisons tend to be biased, since re-implementations of reference methods often lack thoroughness and do not include the hands-on experience obtained during the original development process. This paper presents a thorough comparison of 3D scan registration algorithms based on a 3D mapping field experiment, carried out by two research groups that are leading in the field of 3D robotic mapping. The iterative closest points algorithm (ICP) is compared to the normal distributions transform (NDT). We also present an improved version of NDT with a substantially larger valley of convergence than previously published versions.}, address = {Kobe, Japan}, author = {Magnusson, M. and A. N{\"u}chter, C. L{\"o}rken and Lilienthal, A. J. and Hertzberg, J.}, booktitle = {Proceedings of the IEEE International Conference Robotics and Automation (ICRA '09)}, keywords = {imported}, month = {05}, pages = {3907–3912}, title = {{Evaluation of 3D Registration Reliability and Speed – A Comparison of ICP and NDT}}, year = 2009 }
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  Linearisierte Lösung der ICP-Fehlerfunktion f"ur global konsistentes Scanmatching. Nüchter, A.; Elseberg, J. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2009, Fachhochschule Oldenburg/Ostfr./Whv., pp. 74–81. 2009.
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  Dieser Artikel beschreibt eine Linearisierung in geschlossener Form für die Minimierung der Fehlerfunktion, die beim ICP-Algorithmus auftaucht. Die Linearisierung approximiert die tatsächliche Lösung und nutzt die Annahme aus, dass die auftretenden Winkel klein sind. Weiterhin zeigt der Artikel die Möglichkeit auf, die Linearisierung für global konsistentes Scanmatching zu verwenden. Global konsistentes Scanmatching minimiert den Gesamtfehler, wenn mehr als zwei 3D-Punktwolken vorliegen.

  @inproceedings{3DTage2009, abstract = {Dieser Artikel beschreibt eine Linearisierung in geschlossener Form für die Minimierung der Fehlerfunktion, die beim ICP-Algorithmus auftaucht. Die Linearisierung approximiert die tatsächliche Lösung und nutzt die Annahme aus, dass die auftretenden Winkel klein sind. Weiterhin zeigt der Artikel die Möglichkeit auf, die Linearisierung für global konsistentes Scanmatching zu verwenden. Global konsistentes Scanmatching minimiert den Gesamtfehler, wenn mehr als zwei 3D-Punktwolken vorliegen.}, author = {N{\"u}chter, A. and Elseberg, J.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2009, Fachhochschule Oldenburg/Ostfr./Whv.}, keywords = {myown}, month = {01}, pages = {74–81}, title = {{Linearisierte L{\"o}sung der ICP-Fehlerfunktion f{"u}r global konsistentes Scanmatching}}, year = 2009 }
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  Parallel and Cached Scan Matching for Robotic 3D Mapping. Nüchter, A. In Journal of Computing and Information Technology (eCIT), 17(1), pp. 51–65. 2009.
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  Intelligent autonomous acting of mobile robots in unstructured environments requires 3D maps. Since manual mapping is a tedious job, automatization of this job is necessary. Automatic, consistent volumetric modeling of environments requires a solution to the simultaneous localization and map building problem (SLAM problem). In 3D this task is computationally expensive, since the environments are sampled with many data points with state of the art sensing technology. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper summarizes our 6D SLAM algorithm and presents novel algorithmic and technical means to reduce computation time, i.e., the data structure cached k-d tree and parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics tasks.

  @article{eCIT2009, abstract = {Intelligent autonomous acting of mobile robots in unstructured environments requires 3D maps. Since manual mapping is a tedious job, automatization of this job is necessary. Automatic, consistent volumetric modeling of environments requires a solution to the simultaneous localization and map building problem (SLAM problem). In 3D this task is computationally expensive, since the environments are sampled with many data points with state of the art sensing technology. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper summarizes our 6D SLAM algorithm and presents novel algorithmic and technical means to reduce computation time, i.e., the data structure cached k-d tree and parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics tasks.}, author = {N{\"u}chter, A.}, journal = {Journal of Computing and Information Technology (eCIT)}, keywords = {imported}, month = {03}, number = 1, pages = {51–65}, title = {{Parallel and Cached Scan Matching for Robotic 3D Mapping}}, volume = 17, year = 2009 }
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  GPU-accelerated Nearest Neighbor Search for 3D Registration. Qiu, D.; May, S.; Nüchter, A. In Proceedings of the 7th International Conference on Computer Vision Systems (ICVS ’09), of LNCS, pp. 194–203. Liège, Belgium, 2009.
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  Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly sophisticated search methods and parallelism. We show that NNS based vision algorithms like the Iterative Closest Points algorithm (ICP) can achieve real-time capability while preserving compact size and moderate energy consumption as it is needed in robotics and many other domains. The approach exploits the concept of general purpose computation on graphics processing units (GPGPU) and is compared to parallel processing on CPU. We apply this approach to the 3D scan registration problem, for which a speed-up factor of 88 compared to a sequential CPU implementation is reported.

  @inproceedings{ICVS2009, abstract = {Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly sophisticated search methods and parallelism. We show that NNS based vision algorithms like the Iterative Closest Points algorithm (ICP) can achieve real-time capability while preserving compact size and moderate energy consumption as it is needed in robotics and many other domains. The approach exploits the concept of general purpose computation on graphics processing units (GPGPU) and is compared to parallel processing on CPU. We apply this approach to the 3D scan registration problem, for which a speed-up factor of 88 compared to a sequential CPU implementation is reported.}, address = {Li\`{e}ge, Belgium}, author = {Qiu, D. and May, S. and N{\"u}chter, A.}, booktitle = {Proceedings of the 7th International Conference on Computer Vision Systems (ICVS '09)}, keywords = {imported}, month = 10, number = 5815, pages = {194–203}, series = {LNCS}, title = {{GPU-accelerated Nearest Neighbor Search for 3D Registration}}, year = 2009 }

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  Global Konsistente 3D-Kartierung mit Scanmatching. Nüchter, A.; Lingemann, K.; Bormann, D.; Elseberg, J.; Böhm, J. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2008, Fachhochschule Oldenburg/Ostfr./Whv. 2008.
  • [ Abstract ]
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  Das Einpassen bzw. Registrieren von Punktmengen unter starren Transformationen ist eines der Grundprobleme in der Bildverarbeitung. Hierbei können die 3D-Daten aus Laserscannern, Stereokameras u.ä. stammen. Für zwei 3D-Punktmengen bildet der ICP-Algorithmus (Iterative Closest Points) einen de facto Standard für das Registrieren. Weitet man diesen Algorithmus jedoch auf viele 3D-Scans aus, akkumulieren sich Registrierungsfehler. Der vorliegende Beitrag skizziert einen neuen Algorithmus für das global konsistente 3D-Scanmatching (Borrmann, Elseberg, Lingemann, Nüchter und Hertzberg 2008) und zeigt eine Anwendung für das Erfassen von Gebäuden. Die Genauigkeit des Algorithmus wird bezüglich geodätischer Methoden evaluiert.

  @inproceedings{3DTage2008, abstract = {Das Einpassen bzw. Registrieren von Punktmengen unter starren Transformationen ist eines der Grundprobleme in der Bildverarbeitung. Hierbei können die 3D-Daten aus Laserscannern, Stereokameras u.ä. stammen. Für zwei 3D-Punktmengen bildet der ICP-Algorithmus (Iterative Closest Points) einen de facto Standard für das Registrieren. Weitet man diesen Algorithmus jedoch auf viele 3D-Scans aus, akkumulieren sich Registrierungsfehler. Der vorliegende Beitrag skizziert einen neuen Algorithmus für das global konsistente 3D-Scanmatching (Borrmann, Elseberg, Lingemann, Nüchter und Hertzberg 2008) und zeigt eine Anwendung für das Erfassen von Gebäuden. Die Genauigkeit des Algorithmus wird bezüglich geodätischer Methoden evaluiert.}, author = {N{\"u}chter, A. and Lingemann, K. and Bormann, D. and Elseberg, J. and B{\"o}hm, J.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2008, Fachhochschule Oldenburg/Ostfr./Whv.}, keywords = {myown}, month = {01}, title = {{Global Konsistente 3D-Kartierung mit Scanmatching}}, year = 2008 }
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  Towards Semantic 3D Maps. Nüchter, A.; Hertzberg, J. In Journal Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Knowledge in Robotics, 56(11), pp. 915–926. 2008.
  • [ Abstract ]
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  Intelligent autonomous action in ordinary environments calls for 3D maps. 3D geometry is necessary for avoiding collision with complex obstacles and to self localize in six degrees of freedom (6 DoF) (x, y, z positions, roll, yaw, and pitch angles). Meaning, in addition to geometry, becomes inevitable if the robot is supposed to interact with its environment in a goal-directed way. A semantic stance enables the robot to reason about objects; it helps disambiguate or round off sensor data; and the robot knowledge becomes reviewable and communicable. The paper describes an approach and a completed robot system for semantic mapping. The prime sensor is a 3D laser scanner. Individual scans are registered into a coherent 3D geometry map by 6D SLAM. Coarse scene features (e.g., walls, floors in a building) are determined by semantic labeling. More delicate objects are then detected by a trained classifier and localized. In the end, the semantic maps can be visualized for human inspection. We sketch the overall architecture of the approach, explain the respective steps and their underlying algorithms, give examples based on a working robot implementation, and discuss the findings.

  @article{RAS2008, abstract = {Intelligent autonomous action in ordinary environments calls for 3D maps. 3D geometry is necessary for avoiding collision with complex obstacles and to self localize in six degrees of freedom (6 DoF) (x, y, z positions, roll, yaw, and pitch angles). Meaning, in addition to geometry, becomes inevitable if the robot is supposed to interact with its environment in a goal-directed way. A semantic stance enables the robot to reason about objects; it helps disambiguate or round off sensor data; and the robot knowledge becomes reviewable and communicable. The paper describes an approach and a completed robot system for semantic mapping. The prime sensor is a 3D laser scanner. Individual scans are registered into a coherent 3D geometry map by 6D SLAM. Coarse scene features (e.g., walls, floors in a building) are determined by semantic labeling. More delicate objects are then detected by a trained classifier and localized. In the end, the semantic maps can be visualized for human inspection. We sketch the overall architecture of the approach, explain the respective steps and their underlying algorithms, give examples based on a working robot implementation, and discuss the findings.}, author = {N{\"u}chter, A. and Hertzberg, J.}, journal = {Journal Robotics and Autonomous Systems (JRAS), Special Issue on Semantic Knowledge in Robotics}, keywords = {imported}, month = 11, number = 11, pages = {915–926}, title = {{Towards Semantic 3D Maps}}, volume = 56, year = 2008 }
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  The Efficient Extension of Globally Consistent Scan Matching to 6 DoF. Borrmann, D.; Elseberg, J.; Lingemann, K.; Nüchter, Andreas; Hertzberg, J. In Proceedings of the 4th International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT ’08), pp. 29–36. Atlanta, USA, 2008.
  • [ Abstract ]
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  Over ten years ago, Lu and Milios presented a probabilistic scan matching algorithm for solving the simultaneous localization and mapping (SLAM) problem with 2D laser range scans, a standard in robotics. This paper presents an extension to this GraphSLAM method. Our iterative algorithm uses a sparse network to represent the relations between several overlapping 3D scans, computes in every step the 6 degrees of freedom (DoF) transformation in closed form and exploits efficient data association with cached k-d trees. Our approach leads to globally consistent 3D maps, precise 6D pose and covariance estimates, as demonstrated by various experimental results.

  @inproceedings{3DPVT2008, abstract = {Over ten years ago, Lu and Milios presented a probabilistic scan matching algorithm for solving the simultaneous localization and mapping (SLAM) problem with 2D laser range scans, a standard in robotics. This paper presents an extension to this GraphSLAM method. Our iterative algorithm uses a sparse network to represent the relations between several overlapping 3D scans, computes in every step the 6 degrees of freedom (DoF) transformation in closed form and exploits efficient data association with cached k-d trees. Our approach leads to globally consistent 3D maps, precise 6D pose and covariance estimates, as demonstrated by various experimental results.}, address = {Atlanta, USA}, author = {Borrmann, D. and Elseberg, J. and Lingemann, K. and N{\"u}chter, Andreas and Hertzberg, J.}, booktitle = {Proceedings of the 4th International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '08)}, keywords = {imported}, month = {06}, pages = {29–36}, title = {{The Efficient Extension of Globally Consistent Scan Matching to 6 DoF}}, year = 2008 }
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  Surface Reconstruction for 3D Robotic Mapping. Wiemann, T.; Nüchter, A.; Lingemann, K.; Stiene, S.; Hertzberg, J. In Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS ’08). Nice, France, 2008.
  • [ BibTeX ]
  @inproceedings{WS3DMAP2_2008, address = {Nice, France}, author = {Wiemann, T. and N{\"u}chter, A. and Lingemann, K. and Stiene, S. and Hertzberg, J.}, booktitle = {Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS '08)}, keywords = {myown}, month = {09}, title = {Surface Reconstruction for 3D Robotic Mapping}, year = 2008 }
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  Globally consistent 3D mapping with scan matching. Borrmann, D.; Elseberg, J.; Lingemann, K.; Nüchter, A.; Hertzberg, J. In Journal Robotics and Autonomous Systems (JRAS), 56(2), pp. 130–142. 2008.
  • [ Abstract ]
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  A globally consistent solution to the simultaneous localization and mapping (SLAM) problem in 2D with three degrees of freedom (DoF) poses was presented by Lu and Milios [F. Lu, E. Milios, Globally consistent range scan alignment for environment mapping, Autonomous Robots 4 (April) (1997) 333-349]. To create maps suitable for natural environments it is however necessary to consider the 6DoF pose case, namely the three Cartesian coordinates and the roll, pitch and yaw angles. This article describes the extension of the proposed algorithm to deal with these additional DoFs and the resulting non-linearities. Simplifications using Taylor expansion and Cholesky decomposition yield a fast application that handles the massive amount of 3D data and the computational requirements due to the 6DoF. Our experiments demonstrate the functionality of estimating the exact poses and their covariances in all 6DoF, leading to a globally consistent map. The correspondences between scans are found automatically by use of a simple distance heuristic.

  @article{RAS2007, abstract = {A globally consistent solution to the simultaneous localization and mapping (SLAM) problem in 2D with three degrees of freedom (DoF) poses was presented by Lu and Milios [F. Lu, E. Milios, Globally consistent range scan alignment for environment mapping, Autonomous Robots 4 (April) (1997) 333-349]. To create maps suitable for natural environments it is however necessary to consider the 6DoF pose case, namely the three Cartesian coordinates and the roll, pitch and yaw angles. This article describes the extension of the proposed algorithm to deal with these additional DoFs and the resulting non-linearities. Simplifications using Taylor expansion and Cholesky decomposition yield a fast application that handles the massive amount of 3D data and the computational requirements due to the 6DoF. Our experiments demonstrate the functionality of estimating the exact poses and their covariances in all 6DoF, leading to a globally consistent map. The correspondences between scans are found automatically by use of a simple distance heuristic.}, author = {Borrmann, D. and Elseberg, J. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J.}, journal = {Journal Robotics and Autonomous Systems (JRAS)}, keywords = {imported}, month = {02}, number = 2, pages = {130–142}, title = {Globally consistent 3D mapping with scan matching}, volume = 56, year = 2008 }
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  Does it help a robot navigate to call navigability an affordance?. Hertzberg, J.; Lingemann, K.; Lörken, C.; Nüchter, A.; Stiene, S. In Towards Affordance-Based Robot Control. Proceedings of Dagstuhl Seminar 06231, Dagstuhl Castle, pp. 16–26. Springer LNAI, 2008.
  • [ Abstract ]
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  Gibson’s notion of affordance seems to attract roboticists’ attention. On a phenomenological level, it allows functions, which have “somehow” been implemented, to be described using a new terminology. However, that does not mean that the affordance notion is of help for building robots and their controllers. This paper explores viewing an affordance as an abstraction from a robot-environment relation that is of inter-individual use, but requires an individual implementation. Therefore, the notion of affordance helps share environment representations and theories among robots. Examples are given for navigability, as afforded by environments of different types to robots of different undercarriages and sensor configurations. Work in parts done in the projects (1) LISA, which is funded by the German Federal Ministry of Education and Research (BMBF) within the Framework Concept ”Research for Tomorrow’s Production” (fund number 02PB2170-02PB2177) and managed by the Project Management Agency Forschungszentrum Karlsruhe, Production and Manufacturing Technologies Division (PTKA-PFT); and (2) MACS, which is funded by the European Commission’s 6th Framework Programme IST Project MACS under contract/grant number FP6-004381. The Commission’s support is gratefully acknowledged.

  @incollection{Dagstuhl2008, abstract = {Gibson’s notion of affordance seems to attract roboticists’ attention. On a phenomenological level, it allows functions, which have “somehow” been implemented, to be described using a new terminology. However, that does not mean that the affordance notion is of help for building robots and their controllers. This paper explores viewing an affordance as an abstraction from a robot-environment relation that is of inter-individual use, but requires an individual implementation. Therefore, the notion of affordance helps share environment representations and theories among robots. Examples are given for navigability, as afforded by environments of different types to robots of different undercarriages and sensor configurations. Work in parts done in the projects (1) LISA, which is funded by the German Federal Ministry of Education and Research (BMBF) within the Framework Concept ”Research for Tomorrow’s Production” (fund number 02PB2170-02PB2177) and managed by the Project Management Agency Forschungszentrum Karlsruhe, Production and Manufacturing Technologies Division (PTKA-PFT); and (2) MACS, which is funded by the European Commission’s 6th Framework Programme IST Project MACS under contract/grant number FP6-004381. The Commission’s support is gratefully acknowledged.}, author = {Hertzberg, J. and Lingemann, K. and L{\"o}rken, C. and N{\"u}chter, A. and Stiene, S.}, booktitle = {Towards Affordance-Based Robot Control. Proceedings of Dagstuhl Seminar 06231, Dagstuhl Castle}, keywords = {myown}, pages = {16–26}, publisher = {Springer LNAI}, title = {Does it help a robot navigate to call navigability an affordance?}, year = 2008 }
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  Evaluating a 3D Camera for RoboCup Rescue. Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings of the SICE Annual Conference 2008: International Conference on Instrumentation, Control and Information Technology (SICE ’08), pp. 2070–2075. Tokyo, Japan, 2008.
  • [ Abstract ]
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  The following paper evaluates a time-of-flight 3D camera with regards to its usability for RoboCup rescue. This includes an evaluation of the influence of outer conditions to the camera data, as well as its usage for automatic 3D mapping by scan registration. A color camera is calibrated with respect to the 3D camera in order to gain colored texture information for the acquired measurements.

  @inproceedings{SICE2008, abstract = {The following paper evaluates a time-of-flight 3D camera with regards to its usability for RoboCup rescue. This includes an evaluation of the influence of outer conditions to the camera data, as well as its usage for automatic 3D mapping by scan registration. A color camera is calibrated with respect to the 3D camera in order to gain colored texture information for the acquired measurements.}, address = {Tokyo, Japan}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the SICE Annual Conference 2008: International Conference on Instrumentation, Control and Information Technology (SICE '08)}, keywords = {imported}, month = {08}, pages = {2070–2075}, title = {{Evaluating a 3D Camera for RoboCup Rescue}}, year = 2008 }
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  Benchmarking Urban 6D SLAM. Wulf, O.; Nüchter, A.; Hertzberg, J.; Wagner, B. In Journal of Field Robotics (JFR), 25(3), pp. 148–163. 2008.
  • [ Abstract ]
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  Quite a number of approaches for solving the simultaneous localization and mapping (SLAM) problem exist by now. Some of them have recently been extended to mapping environments with six degrees of freedom (DoF) poses, yielding 6D SLAM approaches. To demonstrate the capabilities of the respective algorithms, it is common practice to present generated maps and successful loop closings in large outdoor environments. Unfortunately, it is non-trivial to compare different 6D SLAM approaches objectively, because ground truth data about the outdoor environments used for demonstration is typically unavailable. We present a novel benchmarking method for generating this ground truth data based on reference maps. The method is then demonstrated by comparing the absolute performance of some previously existing 6D SLAM algorithms which build a large urban outdoor map.

  @article{JFR2007, abstract = {Quite a number of approaches for solving the simultaneous localization and mapping (SLAM) problem exist by now. Some of them have recently been extended to mapping environments with six degrees of freedom (DoF) poses, yielding 6D SLAM approaches. To demonstrate the capabilities of the respective algorithms, it is common practice to present generated maps and successful loop closings in large outdoor environments. Unfortunately, it is non-trivial to compare different 6D SLAM approaches objectively, because ground truth data about the outdoor environments used for demonstration is typically unavailable. We present a novel benchmarking method for generating this ground truth data based on reference maps. The method is then demonstrated by comparing the absolute performance of some previously existing 6D SLAM algorithms which build a large urban outdoor map.}, author = {Wulf, O. and N{\"u}chter, A. and Hertzberg, J. and Wagner, B.}, journal = {Journal of Field Robotics (JFR)}, keywords = {imported}, month = {03}, number = 3, pages = {148–163}, title = {{Benchmarking Urban 6D SLAM}}, volume = 25, year = 2008 }
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  3D Mapping the Kvarntorp Mine: A Field Experiment for Evaluation of 3D Scan Matching Algorithms. Magnusson, M.; Nüchter, A.; Lörken, C.; Lilienthal, A. J.; Hertzberg, J. In Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS ’08). Nice, France, 2008.
  • [ BibTeX ]
  @inproceedings{WS3DMAP1_2008, address = {Nice, France}, author = {Magnusson, M. and N{\"u}chter, A. and L{\"o}rken, C. and Lilienthal, A. J. and Hertzberg, J.}, booktitle = {Proceedings of the Workshop on 3D-Mapping at the IEEE International Conference on Intelligent Robots and Systems (IROS '08)}, keywords = {imported}, month = {09}, title = {3D Mapping the Kvarntorp Mine: A Field Experiment for Evaluation of 3D Scan Matching Algorithms}, year = 2008 }

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  Real-Time Outdoor Trail Detection on a Mobile Robot. Bartel, A.; Meyer, F.; Sinke, C.; Wiemann, T.; Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings of the 13th IASTED International Conference on Robotics and Applications (RA ’07), pp. 477–482. Würzburg, Germany, 2007.
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  In this paper we present a reliable approach for real-time outdoor trail following and obstacle avoidance. The trail classification is done using an off-the-shelf webcam and a pitched 2D laser scanner on a KURT2 robot equipped with an Intel Centrino laptop. This simple setup enables us to follow given pathways of different kinds using a GPS receiver for rough orientation.

  @inproceedings{RA2007_1, abstract = {In this paper we present a reliable approach for real-time outdoor trail following and obstacle avoidance. The trail classification is done using an off-the-shelf webcam and a pitched 2D laser scanner on a KURT2 robot equipped with an Intel Centrino laptop. This simple setup enables us to follow given pathways of different kinds using a GPS receiver for rough orientation.}, address = {W{\"u}rzburg, Germany}, author = {Bartel, A. and Meyer, F. and Sinke, C. and Wiemann, T. and N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the 13th IASTED International Conference on Robotics and Applications (RA '07)}, keywords = {myown}, month = {08}, pages = {477–482}, title = {{Real-Time Outdoor Trail Detection on a Mobile Robot}}, year = 2007 }
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  Algorithmen zur Erstellung virtueller 3D-Welten mit mobilen Robotern. Nüchter, A. In Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beiträge der Oldenburger 3D-Tage 2007, Fachhochschule Oldenburg/Ostfr./Whv. 2007.
  • [ Abstract ]
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  3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreid imensionale Abtasten von Objekten möglich macht. Roboter, die ihre Umgebung dreidimensional kartieren können, eignen sich zum automatischen Erstellen virtuelle 3D-Welten. Eine 3D-Welt, oder 3D-Umgebungskarte muss mit der wirklichen Umgebung übereinstimmen, also korrekt und konsistent sein. Ist die Position des Roboters genau bekannt, können die loka len Karten auf der Grundlage dieser Position zusammengefügt werden. Leider ist die Selbstlokalisation eines Roboters stets fehlerbehaftet. Daher darf der Kartenbau nicht nur auf der Roboterposition basieren, sondern muss auch auf der Grundlage der Sensorwerte geschehen. In diesem Zusammenhang spricht man vom simultanen Lokalisations- und Kartierungs problem (SLAM, simultaneous localization and mapping problem). Korrekte, global konsistente Modelle entstehen durch e inen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erka nnt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus.

  @inproceedings{3DTage2007, abstract = {3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreid imensionale Abtasten von Objekten möglich macht. Roboter, die ihre Umgebung dreidimensional kartieren können, eignen sich zum automatischen Erstellen virtuelle 3D-Welten. Eine 3D-Welt, oder 3D-Umgebungskarte muss mit der wirklichen Umgebung übereinstimmen, also korrekt und konsistent sein. Ist die Position des Roboters genau bekannt, können die loka len Karten auf der Grundlage dieser Position zusammengefügt werden. Leider ist die Selbstlokalisation eines Roboters stets fehlerbehaftet. Daher darf der Kartenbau nicht nur auf der Roboterposition basieren, sondern muss auch auf der Grundlage der Sensorwerte geschehen. In diesem Zusammenhang spricht man vom simultanen Lokalisations- und Kartierungs problem (SLAM, simultaneous localization and mapping problem). Korrekte, global konsistente Modelle entstehen durch e inen 6D-SLAM Algorithmus. Hierbei werden 6 Freiheitsgrade in der Roboterpose berücksichtigt, geschlossene Kreise erka nnt und der globale Fehler minimiert. Die Basis des 6D-SLAM ist ein sehr schneller ICP-Algorithmus.}, author = {N{\"u}chter, A.}, booktitle = {Photogrammetrie Laserscanning Optische 3D-Messtechnik, Beitr{\"a}ge der Oldenburger 3D-Tage 2007, Fachhochschule Oldenburg/Ostfr./Whv.}, keywords = {imported}, month = {01}, title = {{Algorithmen zur Erstellung virtueller 3D-Welten mit mobilen Robotern}}, year = 2007 }
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  Assessing stereo matching algorithms using ground-truth disparity maps of natural scenes. Steger, J.; Märtin, R.; Lingemann, K.; Nüchter, A.; Hertzberg, J.; König, P. In Proceedings of the 7th Meeting of the German Neuroscience Society / 31th Göttingen Neurobiology Conference, Neuroforum 2007. Göttingen, Germany, 2007.
  • [ BibTeX ]
  @inproceedings{NF2007, address = {G{\"o}ttingen, Germany}, author = {Steger, J. and M{\"a}rtin, R. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J. and K{\"o}nig, P.}, booktitle = {Proceedings of the 7th Meeting of the German Neuroscience Society / 31th G{\"o}ttingen Neurobiology Conference, Neuroforum 2007}, keywords = {imported}, month = {03}, title = {{Assessing stereo matching algorithms using ground-truth disparity maps of natural scenes}}, year = 2007 }
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  Parallelization of Scan Matching for Robotic 3D Mapping. Nüchter, A. In Proceedings of the 3rd European Conference on Mobile Robots (ECMR ’07). Freiburg, Germany, 2007.
  • [ Abstract ]
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  Robotic 3D Mapping of environments is computationally expensive, since 3D scanners sample the environment with many data points. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper extends our solution to the 3D mapping problem by parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics task with on-board means.

  @inproceedings{ECMR2007, abstract = {Robotic 3D Mapping of environments is computationally expensive, since 3D scanners sample the environment with many data points. In addition, the solution space grows exponentially with the additional degrees of freedom needed to represent the robot pose. Mapping environments in 3D must regard six degrees of freedom to characterize the robot pose. This paper extends our solution to the 3D mapping problem by parallelization. The availability of multi-core processors as well as efficient programming schemes as OpenMP permit the parallel execution of robotics task with on-board means.}, address = {Freiburg, Germany}, author = {N{\"u}chter, A.}, booktitle = {Proceedings of the 3rd European Conference on Mobile Robots (ECMR '07)}, keywords = {imported}, month = {09}, title = {{Parallelization of Scan Matching for Robotic 3D Mapping}}, year = 2007 }
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  Salient Visual Features to Help Close the Loop in 6D SLAM. Kunze, L.; Lingemann, K.; Nüchter, A.; Hertzberg, J. In Proceedings of the ICVS Workshop on Computational Attention \& Applications (WCAA ’07). Bielefeld, Germany, 2007.
  • [ Abstract ]
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  One fundamental problem in mobile robotics research is Simultaneous Localization and Mapping (SLAM): A mobile robot has to localize itself in an unknown environment, and at the same time generate a map of the surrounding area. One fundamental part of SLAM algorithms is loop closing: The robot detects whether it has reached an area that has been visited before, and uses this information to improve the pose estimate in the next step. In this work, visual camera features are used to assist closing the loop in an existing 6 degree of freedom SLAM (6D SLAM) architecture. For our robotics application we propose and evaluate several detection methods, including salient region detection and maximally stable extremal region detection. The detected regions are encoded using SIFT descriptors and stored in a database. Loops are detected by matching of the images' descriptors. A comparison of the different feature detection methods shows that the combination of salient and maximally stable extremal regions suggested by performs moderately.

  @inproceedings{WCAA2007, abstract = {One fundamental problem in mobile robotics research is Simultaneous Localization and Mapping (SLAM): A mobile robot has to localize itself in an unknown environment, and at the same time generate a map of the surrounding area. One fundamental part of SLAM algorithms is loop closing: The robot detects whether it has reached an area that has been visited before, and uses this information to improve the pose estimate in the next step. In this work, visual camera features are used to assist closing the loop in an existing 6 degree of freedom SLAM (6D SLAM) architecture. For our robotics application we propose and evaluate several detection methods, including salient region detection and maximally stable extremal region detection. The detected regions are encoded using SIFT descriptors and stored in a database. Loops are detected by matching of the images' descriptors. A comparison of the different feature detection methods shows that the combination of salient and maximally stable extremal regions suggested by performs moderately.}, address = {Bielefeld, Germany}, author = {Kunze, L. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J.}, booktitle = {Proceedings of the ICVS Workshop on Computational Attention \& Applications (WCAA '07)}, keywords = {myown}, month = {03}, title = {{Salient Visual Features to Help Close the Loop in 6D SLAM}}, year = 2007 }
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  Cached $k$-d tree search for ICP Algorithms. Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings of the 6th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM ’07), pp. 419–426. Montreal, QC, Canada, 2007.
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  The ICP (iterative closest point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of ICP is the search for closest points. Since the development of ICP, k-d trees have been used to accelerate the search. This paper presents a novel search procedure, namely cached k-d trees, exploiting iterative behavior of the ICP algorithm. It results in a significant speedup of about 50\% as we show in an evaluation using different data sets.

  @inproceedings{3DIM2007, abstract = {The ICP (iterative closest point) algorithm is the de facto standard for geometric alignment of three-dimensional models when an initial relative pose estimate is available. The basis of ICP is the search for closest points. Since the development of ICP, k-d trees have been used to accelerate the search. This paper presents a novel search procedure, namely cached k-d trees, exploiting iterative behavior of the ICP algorithm. It results in a significant speedup of about 50\% as we show in an evaluation using different data sets.}, address = {Montreal, QC, Canada}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the 6th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '07)}, keywords = {myown}, month = {08}, pages = {419–426}, title = {{C}ached $k$-d tree search for {ICP} {A}lgorithms}, year = 2007 }
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  6D SLAM with Cached k-d tree Search. Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings of the 13th IASTED International Conference on Robotics and Applications (RA ’07), pp. 181–186. Würzburg, Germany, 2007.
  • [ Abstract ]
  • [ BibTeX ]
  6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six degrees of freedom for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. In previous work we presented our scan matching based 6D SLAM approach [cite deleted], where scan matching is based on the well known iter ative closest point (ICP) algorithm [3]. Effcient implementations of this algorithm are a result of a fast computation of closest points. The usual approach, i.e., using k-d trees is extended in this paper. We describe a novel search strategy, that lead s to significant speed-ups. Our mapping system is real-time capable, i.e., 3D maps are computed using the resources of the used robotic hardware.

  @inproceedings{RA2007_2, abstract = {6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six degrees of freedom for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. In previous work we presented our scan matching based 6D SLAM approach [cite deleted], where scan matching is based on the well known iter ative closest point (ICP) algorithm [3]. Effcient implementations of this algorithm are a result of a fast computation of closest points. The usual approach, i.e., using k-d trees is extended in this paper. We describe a novel search strategy, that lead s to significant speed-ups. Our mapping system is real-time capable, i.e., 3D maps are computed using the resources of the used robotic hardware.}, address = {W{\"u}rzburg, Germany}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the 13th IASTED International Conference on Robotics and Applications (RA '07)}, keywords = {imported}, month = {08}, pages = {181–186}, title = {{6D SLAM with Cached k-d tree Search}}, year = 2007 }
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  6D SLAM -- 3D Mapping Outdoor Environments. Nüchter, A.; Lingemann, K.; Hertzberg, J.; Surmann, H. In Journal of Field Robotics (JFR), Special Issue on Quantitative Performance Evaluation of Robotic and Intelligent Systems, 24(8--9), pp. 699–722. 2007.
  • [ Abstract ]
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  6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving outdoor with a mobile robot, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Iterative Closest Point (ICP) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system. A new strategy for fast data association, cached kd tree search, leads to feasible computing times. With no ground-truth data available for outdoor environments, point relations in maps are compared to numerical relations in uncalibrated aerial images in order to assess the metric validity of the resulting 3D maps.

  @article{JFR2006, abstract = {6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving outdoor with a mobile robot, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Iterative Closest Point (ICP) scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system. A new strategy for fast data association, cached kd tree search, leads to feasible computing times. With no ground-truth data available for outdoor environments, point relations in maps are compared to numerical relations in uncalibrated aerial images in order to assess the metric validity of the resulting 3D maps.}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Surmann, H.}, journal = {Journal of Field Robotics (JFR), Special Issue on Quantitative Performance Evaluation of Robotic and Intelligent Systems}, keywords = {imported}, month = {08}, number = {8–9}, pages = {699–722}, title = {{6D SLAM – 3D Mapping Outdoor Environments}}, volume = 24, year = 2007 }
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  Laser range scans of natural scenes for the evaluation of stereo-matching algorithms. Steger, J.; Märtin, R.; Lingemann, K.; Nüchter, A.; Hertzberg, J.; König, P. In Poster at ICVS Workshop From Computational Cognitive Neuroscience to Computer Vision (CCNCV ’07). Bielefeld, Germany, 2007.
  • [ BibTeX ]
  @inproceedings{CCNCV2007, address = {Bielefeld, Germany}, author = {Steger, J. and M{\"a}rtin, R. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J. and K{\"o}nig, P.}, booktitle = {Poster at ICVS Workshop From Computational Cognitive Neuroscience to Computer Vision (CCNCV '07)}, keywords = {imported}, month = {03}, title = {{Laser range scans of natural scenes for the evaluation of stereo-matching algorithms}}, year = 2007 }
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  6D SLAM with Kurt3D. Nüchter, A.; Lingemann, K.; Hertzberg, J. In Robotics Today, Society of Manufacturing Engineers, First Quater, 20(1). 2007.
  • [ BibTeX ]
  @article{RT2007, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, journal = {Robotics Today, Society of Manufacturing Engineers, First Quater}, keywords = {myown}, month = {04}, number = 1, title = {{6D SLAM with Kurt3D}}, volume = 20, year = 2007 }
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  High Speed Differential Drive Mobile Robot Path Following Control With Bounded Wheel Speed Commands. Indiveri, G.; Nüchter, A.; Lingemann, K. In Proceedings of the IEEE International Conference Robotics and Automation (ICRA ’07), pp. 2202–2207. Rome, Italy, 2007.
  • [ Abstract ]
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  The great majority of path following control laws for either kinematical or dynamical mobile robot models are designed assuming ideal actuators, i.e. assuming that any commanded velocity or torque (in the kinematical and dynamical cases respectively) will be instantly implemented regardless of its value. Real actuators are far from being ideal. In particular, only bounded velocities and torques can be realized for any given command. With reference to the kinematical model of a differential drive mobile robot, a known path following control law is modified to account for actuator velocity saturation. The proposed solution is experimentally shown to be particularly useful for high speed applications where accounting for actuator velocity saturation may have a large influence on performance.

  @inproceedings{ICRA2007, abstract = {The great majority of path following control laws for either kinematical or dynamical mobile robot models are designed assuming ideal actuators, i.e. assuming that any commanded velocity or torque (in the kinematical and dynamical cases respectively) will be instantly implemented regardless of its value. Real actuators are far from being ideal. In particular, only bounded velocities and torques can be realized for any given command. With reference to the kinematical model of a differential drive mobile robot, a known path following control law is modified to account for actuator velocity saturation. The proposed solution is experimentally shown to be particularly useful for high speed applications where accounting for actuator velocity saturation may have a large influence on performance.}, address = {Rome, Italy}, author = {Indiveri, G. and N{\"u}chter, A. and Lingemann, K.}, booktitle = {Proceedings of the IEEE International Conference Robotics and Automation (ICRA '07)}, keywords = {myown}, month = {04}, pages = {2202–2207}, title = {High Speed Differential Drive Mobile Robot Path Following Control With Bounded Wheel Speed Commands}, year = 2007 }
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  Ground Truth Evaluation of Large Urban 6D SLAM. Wulf, O.; Nüchter, A.; Hertzberg, J.; Wagner, B. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’07), pp. 650–657. San Diego, CA, USA, 2007.
  • [ Abstract ]
  • [ BibTeX ]
  • [ URL ]
  • [ DOI ]
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  In the past many solutions for simultaneous localization and mapping (SLAM) have been presented. Recently these solutions have been extended to map large environments with six degrees of freedom (DoF) poses. To demonstrate the capabilities of these SLAM algorithms it is common practice to present the generated maps and successful loop closing. Unfortunately there is often no objective performance metric that allows to compare different approaches. This fact is attributed to the lack of ground truth data. For this reason we present a novel method that is able to generate this ground truth data based on reference maps. Further on, the resulting reference path is used to measure the absolute performance of different 6D SLAM algorithms building a large urban outdoor map.

  @inproceedings{IROS2007, abstract = {In the past many solutions for simultaneous localization and mapping (SLAM) have been presented. Recently these solutions have been extended to map large environments with six degrees of freedom (DoF) poses. To demonstrate the capabilities of these SLAM algorithms it is common practice to present the generated maps and successful loop closing. Unfortunately there is often no objective performance metric that allows to compare different approaches. This fact is attributed to the lack of ground truth data. For this reason we present a novel method that is able to generate this ground truth data based on reference maps. Further on, the resulting reference path is used to measure the absolute performance of different 6D SLAM algorithms building a large urban outdoor map.}, address = {San Diego, CA, USA}, author = {Wulf, O. and N{\"u}chter, A. and Hertzberg, J. and Wagner, B.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '07)}, keywords = {imported}, month = 10, pages = {650–657}, title = {Ground Truth Evaluation of Large Urban 6D SLAM}, year = 2007 }
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  Performance of 6D LuM and FFS SLAM -- An Example for Comparison using Grid and Pose Based Evaluation Methods. Lakaemper, R.; Nüchter, A.; Adluru, N.; Latecki, L. J. In Proceedings of seventh workshop on Performance Metrics for Intelligent Systems (PerMIS ’07). Washington D.C., USA, 2007.
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  The focus of this paper is on the performance comparison of two simultaneous localization and mapping (SLAM) algorithms namely 6D Lu/Milios SLAM and Force Field Simulation (FFS). The two algorithms are applied to a 2D data set. Although the algorithms generate overall visually comparable results, they show strengths and weaknesses in different regions of the generated global maps. The question we address in this paper is, if different ways of evaluating the performance of SLAM algorithms project different strengths and how can the evaluations be useful in selecting an algorithm. We will compare the performance of the algorithms in different ways, using grid and pose based quality measures.

  @inproceedings{PERMIS2007, abstract = {The focus of this paper is on the performance comparison of two simultaneous localization and mapping (SLAM) algorithms namely 6D Lu/Milios SLAM and Force Field Simulation (FFS). The two algorithms are applied to a 2D data set. Although the algorithms generate overall visually comparable results, they show strengths and weaknesses in different regions of the generated global maps. The question we address in this paper is, if different ways of evaluating the performance of SLAM algorithms project different strengths and how can the evaluations be useful in selecting an algorithm. We will compare the performance of the algorithms in different ways, using grid and pose based quality measures.}, address = {Washington D.C., USA,}, author = {Lakaemper, R. and N{\"u}chter, A. and Adluru, N. and Latecki, L. J.}, booktitle = {Proceedings of seventh workshop on Performance Metrics for Intelligent Systems (PerMIS '07)}, keywords = {myown}, month = {08}, title = {Performance of 6D LuM and FFS SLAM – An Example for Comparison using Grid and Pose Based Evaluation Methods}, year = 2007 }
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  An Experiment in Semantic Correction of Sensor Data. Stiene, S.; Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings Workshop on Semantic Information in Robotics at the IEEE International Conference Robotics and Automation (ICRA ’07). Rome, Italy, 2007.
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  @inproceedings{ICRA2007WS, address = {Rome, Italy}, author = {Stiene, S. and N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings Workshop on Semantic Information in Robotics at the IEEE International Conference Robotics and Automation (ICRA '07)}, keywords = {myown}, month = {04}, title = {An Experiment in Semantic Correction of Sensor Data}, year = 2007 }

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  Device Level Simulation of Kurt3D Rescue Robots. Albrecht, S.; Hertzberg, J.; Lingemann, K.; Nüchter, A.; Sprickerhof, J.; Stiene, S. In Proceedings of the 3rd International Workshop on Synthetic Simulation and Robotics to Mitigate Earthquake Disaster (SRMED 2006). 2006.
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  USARSIM is a worldwide used robot simulator deployed in Urban Search and Rescue (USAR) and in the context of the RoboCup Rescue Real Robot contest. This paper describes the USARSIM simulator for KURT2 and Kurt3D robot platforms, which we are using in both education and research. As it simulates on the device level, a seamless integration of real robot control software with the simulations becomes possible. We evaluate the performance for simulating laser range scans and the camera system. In addition, we show a simulation of the rescue robots.

  @inproceedings{SRMED2006, abstract = {USARSIM is a worldwide used robot simulator deployed in Urban Search and Rescue (USAR) and in the context of the RoboCup Rescue Real Robot contest. This paper describes the USARSIM simulator for KURT2 and Kurt3D robot platforms, which we are using in both education and research. As it simulates on the device level, a seamless integration of real robot control software with the simulations becomes possible. We evaluate the performance for simulating laser range scans and the camera system. In addition, we show a simulation of the rescue robots.}, author = {Albrecht, S. and Hertzberg, J. and Lingemann, K. and N{\"u}chter, A. and Sprickerhof, J. and Stiene, S.}, booktitle = {Proceedings of the 3rd International Workshop on Synthetic Simulation and Robotics to Mitigate Earthquake Disaster (SRMED 2006)}, keywords = {imported}, month = {06}, title = {{Device Level Simulation of Kurt3D Rescue Robots}}, year = 2006 }
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  Contour-based Object Detection in Range Images. Stiene, S.; Lingemann, K.; Nüchter, A.; Hertzberg, J. In Proceedings of the 3rd IEEE International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT ’06). 2006.
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  This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extraction. Silhouette or contour descriptions are good sources of information for object recognition. We propose a complete object recognition system, based on a 3D laser scanner, reliable contour extraction with floor interpretation, feature extraction using a new, fast eigen-CSS method, and a supervised learning algorithm. The recognition system was successfully tested on range images acquired with a mobile robot, and the results are compared to standard techniques, i.e., geometric features, Hu and Zernike moments, the border signature method and the angular radial transformation. An evaluation using the receiver operating characteristic analysis completes this paper. The eigen-CSS method has proved to be comparable in detection performance to the top competitors, yet faster than the best one by an order of magnitude in feature extraction time.

  @inproceedings{3DPVT2006, abstract = {This paper presents a novel object recognition approach based on range images. Due to its insensitivity to illumination, range data is well suited for reliable silhouette extraction. Silhouette or contour descriptions are good sources of information for object recognition. We propose a complete object recognition system, based on a 3D laser scanner, reliable contour extraction with floor interpretation, feature extraction using a new, fast eigen-CSS method, and a supervised learning algorithm. The recognition system was successfully tested on range images acquired with a mobile robot, and the results are compared to standard techniques, i.e., geometric features, Hu and Zernike moments, the border signature method and the angular radial transformation. An evaluation using the receiver operating characteristic analysis completes this paper. The eigen-CSS method has proved to be comparable in detection performance to the top competitors, yet faster than the best one by an order of magnitude in feature extraction time.}, author = {Stiene, S. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J.}, booktitle = {Proceedings of the 3rd IEEE International Symposium on 3D Data Processing, Visualization and Transmission (3DPVT '06)}, keywords = {imported}, month = {06}, title = {{Contour-based Object Detection in Range Images}}, year = 2006 }
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  Extracting Drivable Surfaces in Outdoor 6D SLAM. Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings of the 37rd International Symposium on Robotics (ISR ’06) and Robotik 2006. Munich, Germany, 2006.
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  A basic issue of mobile robotics is generating environment maps automatically. Outdoor terrain is challenging since the ground is uneven and the surrounding is structured irregularly. In earlier work, we have introduced 6D SLAM (Simultaneous Localization and Mapping) as a method to taking all six DOF of robot poses (x, y, z translation; roll, pitch, yaw angles) into account. This paper adds to 6D SLAM a method for extracting drivable surfaces in the 3D maps while they are being generated. Experiments have been made in a Botanical Garden, with drivable surfaces consisting of gravel paths or lawn, both involving significant slope.

  @inproceedings{ISR2006, abstract = {A basic issue of mobile robotics is generating environment maps automatically. Outdoor terrain is challenging since the ground is uneven and the surrounding is structured irregularly. In earlier work, we have introduced 6D SLAM (Simultaneous Localization and Mapping) as a method to taking all six DOF of robot poses (x, y, z translation; roll, pitch, yaw angles) into account. This paper adds to 6D SLAM a method for extracting drivable surfaces in the 3D maps while they are being generated. Experiments have been made in a Botanical Garden, with drivable surfaces consisting of gravel paths or lawn, both involving significant slope.}, address = {Munich, Germany}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the 37rd International Symposium on Robotics (ISR '06) and Robotik 2006}, keywords = {imported}, month = {05}, title = {{Extracting Drivable Surfaces in Outdoor 6D SLAM}}, year = 2006 }
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  Kurt3D -- A Mobile Robot for 3D Mapping of Environments. Nüchter, A.; Lingemann, K.; Hertzberg, J. ELROB, Hammelburg, Germany, 2006.
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  The mobile robot Kurt3D is the first robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. Kurt3D creates a consistent volumetric scene in a common coordinate frame from multiple 3D laser scans. To create 3D volumetric maps it is necessary to gage several 3D scans and register them into one consistent 3D model. A fast variant of the Iterative Closest Points (ICP) algorithm is used for registration and relocalization.

  @techreport{ELROB2006, abstract = {The mobile robot Kurt3D is the first robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. Kurt3D creates a consistent volumetric scene in a common coordinate frame from multiple 3D laser scans. To create 3D volumetric maps it is necessary to gage several 3D scans and register them into one consistent 3D model. A fast variant of the Iterative Closest Points (ICP) algorithm is used for registration and relocalization.}, address = {Hammelburg, Germany}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, institution = {ELROB}, keywords = {myown}, month = {05}, title = {{Kurt3D – A Mobile Robot for 3D Mapping of Environments}}, year = 2006 }
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  RoboCupRescue - Robot League Team, Team Deutschland1. Lingemann, K.; Nüchter, A.; Wulf, O.; Surmann, H.; Pervölz, K.; Hertzberg, J.; Wagner, B.; Christaller, T. Team Description Paper, Rescue Robot League Competition, Bremen, Germany, 2006.
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  After scoring second in RoboCup Rescue 2004 with Kurt3D and participating in 2005 with two robots, namely Kurt3D and RTS Crawler, we concentrated on the development of interaction between both vehicles. Kurt3D is able to autonomously explore and map the environment in 3D and search for victims. The RTS Crawler is designed to access more demanding territory (i.e., red arena), working either remote controlled or semi-autonomous. The key innovation of this system lies in the capability for autonomous 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes, combined with the intelligent cooperation between robots that enables one operator to efficiently map and explore the whole arena. The robots are equipped with dedicated state of the art equipment, e.g., 3D laser range finders, infrared camera and CO2-sensor. Robots as well as operator station are rather compact and easy to set up. The challenge of controlling two rescue robots with only one operator is managed with a redesigned user interface and a number of autonomous and semi-autonomous features.

  @techreport{TDP2006, abstract = {After scoring second in RoboCup Rescue 2004 with Kurt3D and participating in 2005 with two robots, namely Kurt3D and RTS Crawler, we concentrated on the development of interaction between both vehicles. Kurt3D is able to autonomously explore and map the environment in 3D and search for victims. The RTS Crawler is designed to access more demanding territory (i.e., red arena), working either remote controlled or semi-autonomous. The key innovation of this system lies in the capability for autonomous 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes, combined with the intelligent cooperation between robots that enables one operator to efficiently map and explore the whole arena. The robots are equipped with dedicated state of the art equipment, e.g., 3D laser range finders, infrared camera and CO2-sensor. Robots as well as operator station are rather compact and easy to set up. The challenge of controlling two rescue robots with only one operator is managed with a redesigned user interface and a number of autonomous and semi-autonomous features.}, address = {Bremen, Germany}, author = {Lingemann, K. and N{\"u}chter, A. and Wulf, O. and Surmann, H. and Perv{\"o}lz, K. and Hertzberg, J. and Wagner, B. and Christaller, T.}, institution = {{Team Description Paper, Rescue Robot League Competition}}, keywords = {myown}, month = {06}, title = {{RoboCupRescue - Robot League Team, Team Deutschland1}}, year = 2006 }
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  The RoboCup Rescue Team Deutschland1. Nüchter, A.; Lingemann, K.; Hertzberg, J.; Wulf, O.; Wagner, B.; Pervölz, K.; Surmann, H.; Christaller, T. In KI -- Künstliche Intelligenz, (2), pp. 24–29. 2006.
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  The RoboCup Rescue competition aims at boosting research in robots and infrastructure able to help in real rescue missions. The task is to find and report victims in areas of different grades of roughness, which are currently indoor. It challenges to some extreme the mobility of robot platforms as well as the autonomy of their control and sensor interpretation software. In the 2004 competition, the Kurt3D robot was introduced, the first participant capable of mapping its environment in 3D and self-localizing in all six degrees of freedom, i.e., x, y, z positions and roll, yaw and pitch angles. In 2005, we have upgraded the system with more sensors, with a focus on speeding up the algorithms, and we have started to develop a tracked robot platform to cooperate with Kurt3D. This paper gives an introduction to the competition in general and presents main contributions of our Deutschland1 RoboCup Rescue team.

  @article{KI2006, abstract = {The RoboCup Rescue competition aims at boosting research in robots and infrastructure able to help in real rescue missions. The task is to find and report victims in areas of different grades of roughness, which are currently indoor. It challenges to some extreme the mobility of robot platforms as well as the autonomy of their control and sensor interpretation software. In the 2004 competition, the Kurt3D robot was introduced, the first participant capable of mapping its environment in 3D and self-localizing in all six degrees of freedom, i.e., x, y, z positions and roll, yaw and pitch angles. In 2005, we have upgraded the system with more sensors, with a focus on speeding up the algorithms, and we have started to develop a tracked robot platform to cooperate with Kurt3D. This paper gives an introduction to the competition in general and presents main contributions of our Deutschland1 RoboCup Rescue team.}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Wulf, O. and Wagner, B. and Perv{\"o}lz, K. and Surmann, H. and Christaller, T.}, journal = {KI – K{\"u}nstliche Intelligenz}, keywords = {myown}, number = 2, pages = {24–29}, title = {{The RoboCup Rescue Team Deutschland1}}, year = 2006 }
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  6D SLAM with Kurt3D. Nüchter, A.; Lingemann, K.; Hertzberg, J. In Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition. Bremen, Germany, 2006.
  • [ Abstract ]
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  6D SLAM (Simultaneous Localization and Mapping) of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.

  @inproceedings{3DEnvCog2006_1, abstract = {6D SLAM (Simultaneous Localization and Mapping) of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.}, address = {Bremen, Germany}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {{Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition}}, keywords = {myown}, month = {09}, title = {{6D SLAM with Kurt3D}}, year = 2006 }
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  Semantische dreidimensionale Karten für autonome mobile Roboter. Nüchter, A. In of DISKI, Dissertationen zur künstlichen Intelligenz. Infinix / Aka Verlag, Berlin, Germany, 2006.
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  @book{DISS2006, address = {Berlin, Germany}, author = {N{\"u}chter, A.}, keywords = {imported}, month = 11, number = 303, publisher = {Infinix / Aka Verlag}, series = {DISKI, Dissertationen zur k{\"u}nstlichen Intelligenz}, title = {Semantische dreidimensionale Karten f{\"u}r autonome mobile Roboter}, year = 2006 }
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  Online searching with an autonomous robot. Fekete, S. P.; Klein, R.; Nüchter, A. In Computational Geometry: Theory and Applications (CGTA), 34(2), pp. 102–115. 2006.
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  We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning trajectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.

  @article{CGTA_2006, abstract = {We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning trajectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.}, author = {Fekete, S. P. and Klein, R. and N{\"u}chter, A.}, journal = {Computational Geometry: Theory and Applications (CGTA)}, keywords = {myown}, month = {05}, number = 2, pages = {102–115}, title = {Online searching with an autonomous robot}, volume = 34, year = 2006 }
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  Heuristic-Based Laser Scan Matching for Outdoor 6D SLAM. Nüchter, A.; Lingemann, K.; Hertzberg, J.; Surmann, H. In Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR ’06). Gaithersburg, Maryland, 2006.
  • [ Abstract ]
  • [ BibTeX ]
  6D SLAM (Simultaneous Localization and Mapping) of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.

  @inproceedings{SSRR2006, abstract = {6D SLAM (Simultaneous Localization and Mapping) of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., when driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.}, address = {Gaithersburg, Maryland}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Surmann, H.}, booktitle = {Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR '06)}, keywords = {myown}, month = {08}, title = {{Heuristic-Based Laser Scan Matching for Outdoor 6D SLAM}}, year = 2006 }
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  Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition. Nüchter, A.; Lingemann, K.; Wulf, O. (Online Proceedings), Bremen, Germany, 2006.
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  @proceedings{3DEnvCog2006, address = {Bremen, Germany}, editor = {N{\"u}chter, A. and Lingemann, K. and Wulf, O.}, keywords = {myown}, month = {09}, publisher = {(Online Proceedings)}, title = {Robotic 3D Environment Cognition, Workshop at the International Conference Spatial Cognition}, year = 2006 }

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  Mapping of Rescue Environments with Kurt3D. Nüchter, A.; Lingemann, K.; Hertzberg, J.; Surmann, H.; Pervölz, K.; Hennig, M.; Tiruchinapalli, K. R.; Worst, R.; Christaller, T. In Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR ’05), pp. 158–163. Kobe, Japan, 2005.
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  Deploying rescue workers in an urban setting is often a perilous, time-, power-, and force-consuming job, and systems to assist in this effort are needed. A fundamental task for rescue is to localize injured persons. To this end, robotic systems are used for mapping a site and for remote inspection of suspicious objects. The mobile robot Kurt3D is the first rescue robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles.

  @inproceedings{SSRR2005, abstract = {Deploying rescue workers in an urban setting is often a perilous, time-, power-, and force-consuming job, and systems to assist in this effort are needed. A fundamental task for rescue is to localize injured persons. To this end, robotic systems are used for mapping a site and for remote inspection of suspicious objects. The mobile robot Kurt3D is the first rescue robot that is capable of mapping its environment in 3D and self localize in all six degrees of freedom, i.e., considering its x, y and z positions and the roll, yaw and pitch angles.}, address = {Kobe, Japan}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Surmann, H. and Perv{\"o}lz, K. and Hennig, M. and Tiruchinapalli, K. R. and Worst, R. and Christaller, T.}, booktitle = {Proceedings of the IEEE International Workshop on Safety, Security and Rescue Robotics (SSRR '05)}, keywords = {imported}, month = {06}, pages = {158–163}, title = {{M}apping of {R}escue {E}nvironments with {Kurt3D}}, year = 2005 }
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  Verfahren zur Ermittlung der Position und Orientierung eines navigierenden Systems. Lingemann, K.; Surmann, H.; Nüchter, A.; Hertzberg, J. In Patentblatt, Offenlegungsschrift DE 10 2004 015 111 A1 2005.10.20, 125(42). Deutsches Patentamt, 2005.
  • [ Abstract ]
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  Bei dem Verfahren zur Ermittlung der Position und Orientierung eines autonom navigierenden Systems, beispielsweise eines Roboters, in einer Umgebung werden die Entfernung des in Fahrtrichtung vor den navigierenden System liegenden Bereichs der Umgebung bei Bewegung des navigierenden Systems abgetastet und die abgetasteten Entfernungspunkte mindestens zweier aufeinanderfolgender Abtastvorgänge als Entfernungsmesskurven in der Polardarstellung gespeichert. Anschliessend werden die Entfernungsmesskurven der beiden aufeinander folgenden Abtastvorgänge auf charakteristische merkmale wie z.B. Extremwerte untersucht. Danach werden die parameter von einender getrennt durchführbaren Translations- und Rotationstransformationen der einen Entfernungsmesskurve zur Ermittlungder zuordnung der charakteristischen Merkmale der trnasformierten Entfernungsmesskurve zu solchen der anderen Entfernungsmesskurve und die Position und Orientierung des navigierenden Systems anhand von dessen Position und dessen Orientierung zum Zeitpunkt des zeitlich ersten von zwei aufeinanderfolgenden Abtastungen sowie der ermittelten Parameter der Translation- und Rotationstransformation bestimmt.

  @article{PATENT2005, abstract = {Bei dem Verfahren zur Ermittlung der Position und Orientierung eines autonom navigierenden Systems, beispielsweise eines Roboters, in einer Umgebung werden die Entfernung des in Fahrtrichtung vor den navigierenden System liegenden Bereichs der Umgebung bei Bewegung des navigierenden Systems abgetastet und die abgetasteten Entfernungspunkte mindestens zweier aufeinanderfolgender Abtastvorgänge als Entfernungsmesskurven in der Polardarstellung gespeichert. Anschliessend werden die Entfernungsmesskurven der beiden aufeinander folgenden Abtastvorgänge auf charakteristische merkmale wie z.B. Extremwerte untersucht. Danach werden die parameter von einender getrennt durchführbaren Translations- und Rotationstransformationen der einen Entfernungsmesskurve zur Ermittlungder zuordnung der charakteristischen Merkmale der trnasformierten Entfernungsmesskurve zu solchen der anderen Entfernungsmesskurve und die Position und Orientierung des navigierenden Systems anhand von dessen Position und dessen Orientierung zum Zeitpunkt des zeitlich ersten von zwei aufeinanderfolgenden Abtastungen sowie der ermittelten Parameter der Translation- und Rotationstransformation bestimmt.}, author = {Lingemann, K. and Surmann, H. and N{\"u}chter, A. and Hertzberg, J.}, journal = {Patentblatt, Offenlegungsschrift DE 10 2004 015 111 A1 2005.10.20}, keywords = {imported}, month = 10, number = 42, publisher = {Deutsches Patentamt}, title = {Verfahren zur Ermittlung der Position und Orientierung eines navigierenden Systems}, volume = 125, year = 2005 }
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  3D Mapping with Semantic Knowledge. Nüchter, A.; Wulf, O.; Lingemann, K.; Hertzberg, J.; Wagner, B.; Surmann, H. In Proceedings of the RoboCup International Symposium. Osaka, Japan, 2005.
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  A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360 . The matching is based on semantic information. Surface attributes are extracted and incorporated in a forest of search trees in order to associate the data, i.e., to establish correspondences. The new approach results in advances in speed and reliability.

  @inproceedings{ROBOCUP2005, abstract = {A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360 . The matching is based on semantic information. Surface attributes are extracted and incorporated in a forest of search trees in order to associate the data, i.e., to establish correspondences. The new approach results in advances in speed and reliability.}, address = {Osaka, Japan}, author = {N{\"u}chter, A. and Wulf, O. and Lingemann, K. and Hertzberg, J. and Wagner, B. and Surmann, H.}, booktitle = {Proceedings of the RoboCup International Symposium}, keywords = {imported}, month = {06}, title = {{3D} {M}apping with {S}emantic {K}nowledge}, year = 2005 }
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  High-Speed Laser Localization for Mobile Robots. Lingemann, K.; Nüchter, A.; Hertzberg, J.; Surmann, H. In Journal Robotics and Autonomous Systems (JRAS), 51(4), pp. 275–296. 2005.
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  This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computation time. The efficiency is achieved by a closed-form solution for the matching of two laser scans, the use of natural scan features and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.

  @article{RAS2005, abstract = {This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computation time. The efficiency is achieved by a closed-form solution for the matching of two laser scans, the use of natural scan features and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.}, author = {Lingemann, K. and N{\"u}chter, A. and Hertzberg, J. and Surmann, H.}, journal = {Journal Robotics and Autonomous Systems (JRAS)}, keywords = {imported}, number = 4, pages = {275–296}, title = {High-{S}peed {L}aser {L}ocalization for {M}obile {R}obots}, volume = 51, year = 2005 }
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  Heuristic-Based Laser Scan Matching for Outdoor 6D SLAM. Nüchter, A.; Lingemann, K.; Hertzberg, J.; Surmann, H. In KI 2005: Advances in Artificial Intelligence. 28th Annual German Conference on AI, Proceedings Springer LNAI vol. 3698, pp. 304–319. Koblenz, Germany, 2005.
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  6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.

  @inproceedings{KI2005, abstract = {6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent Localization and Mapping of mobile robots considers six dimensions for the robot pose, namely, the x, y and z coordinates and the roll, yaw and pitch angles. Robot motion and localization on natural surfaces, e.g., driving with a mobile robot outdoor, must regard these degrees of freedom. This paper presents a robotic mapping method based on locally consistent 3D laser range scans. Scan matching, combined with a heuristic for closed loop detection and a global relaxation method, results in a highly precise mapping system for outdoor environments. The mobile robot Kurt3D was used to acquire data of the Schloss Birlinghoven campus. The resulting 3D map is compared with ground truth, given by an aerial photograph.}, address = {Koblenz, Germany}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Surmann, H.}, booktitle = {KI 2005: Advances in Artificial Intelligence. 28th Annual German Conference on AI, Proceedings Springer LNAI vol. 3698}, keywords = {myown}, month = {09}, pages = {304–319}, title = {{H}euristic-{B}ased {L}aser {S}can {M}atching for {O}utdoor {6D} {SLAM}}, year = 2005 }
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  USARSIM -- Game-Engines in der Robotik-Lehre. Hertzberg, J.; Lingemann, K.; Nüchter, A. In Informatik 2005 -- Informatik LIVE, vol.1 (Beiträge der 35. Jahrestagung der Gesellschaft für Informatik, Bonn), pp. 158–162. Bonn, Germany, 2005.
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  In der Lehre zum Thema Wissensbasierte Robotik verwenden wir seit Kurzem den Robotersimulator USARSIM, der weltweit im Kontext der RoboCup Rescue Real Robot Liga eingesetzt wird. Wir stellen den Lehr-Kontext vor, in dem wir arbeiten, skizzieren den Simulator und beschreiben seine Einbindung in unsere Lehre. Unsere Erfahrungen bezuglich der Motivation der Studierenden und ihrer Leistungen der Verwendung des Simulators sind sehr positiv.

  @inproceedings{RIIA2005, abstract = {In der Lehre zum Thema Wissensbasierte Robotik verwenden wir seit Kurzem den Robotersimulator USARSIM, der weltweit im Kontext der RoboCup Rescue Real Robot Liga eingesetzt wird. Wir stellen den Lehr-Kontext vor, in dem wir arbeiten, skizzieren den Simulator und beschreiben seine Einbindung in unsere Lehre. Unsere Erfahrungen bezuglich der Motivation der Studierenden und ihrer Leistungen der Verwendung des Simulators sind sehr positiv.}, address = {Bonn, Germany}, author = {Hertzberg, J. and Lingemann, K. and N{\"u}chter, A.}, booktitle = {Informatik 2005 – Informatik LIVE, vol.1 (Beitr{\"a}ge der 35. Jahrestagung der Gesellschaft f{\"u}r Informatik, Bonn)}, keywords = {imported}, month = {09}, pages = {158–162}, title = {{USARSIM – Game-Engines in der Robotik-Lehre}}, year = 2005 }
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  About the Control of High Speed Mobile Indoor Robots. Lingemann, K.; Nüchter, A.; Hertzberg, J.; Surmann, H. In Proceedings of the Second European Conference on Mobile Robotics (ECMR ’05), pp. 218–223. Ancona, Italy, 2005.
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  This paper describes the control algorithms of the high speed mobile robot Kurt3D. Kurt3D drives up to 4 m/s autonomously and reliably in an unknown office environment. We present the reliable hardware, fast control cycle algorithms and a novel set value computation scheme for achieving these velocities. In addition we sketch a real-time capable laser based position tracking method that is well suited for driving with these velocities.

  @inproceedings{ECMR2005, abstract = {This paper describes the control algorithms of the high speed mobile robot Kurt3D. Kurt3D drives up to 4 m/s autonomously and reliably in an unknown office environment. We present the reliable hardware, fast control cycle algorithms and a novel set value computation scheme for achieving these velocities. In addition we sketch a real-time capable laser based position tracking method that is well suited for driving with these velocities.}, address = {Ancona, Italy}, author = {Lingemann, K. and N{\"u}chter, A. and Hertzberg, J. and Surmann, H.}, booktitle = {Proceedings of the Second European Conference on Mobile Robotics (ECMR '05)}, keywords = {myown}, month = {09}, pages = {218–223}, title = {{A}bout the {C}ontrol of {H}igh {S}peed {M}obile {I}ndoor {R}obots}, year = 2005 }
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  A Bimodal Laser-Based Attention System. Frintrop, S.; Rome, E.; Nüchter, A.; Surmann, H. In Journal Computer Vision and Image Understanding (CVIU), Special Issue on Attention and Performance in Computer Vision, 100(1-2), pp. 124–151. 2005.
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  In this paper, we present a new bimodal attention system for robotic applications capable of processing data from different sensor modes simultaneously. Considering several sensor modalities is an obvious approach to regard a variety of ob ject properties. Nevertheless, conventional att ention systems only regard the processing of camera images. In contrast to these systems, the input data to our system is provided by a bimodal 3D laser scanner, mounted on top of an autonomous mobile robot. In a single 3D scan pass, the scanner yields range as well as reflectance data. Both dat a modes are illumination independent, yielding a robust approach that enables all day operation. Data from both laser modes are fed into our attention system built on principles of one of the standard models of visual attention by Koch & Ullman. The system computes conspicuities of both modes in parallel and fuses them into one saliency map. The focus of attention is directed to the most salient points in this map sequentially. We present results on recorded scans of indoor and outdoor scenes showing the respective advantages of the sensor modalities enabling the mode-specific detectio n of different ob ject properties. Furthermore, we show as an application of the attention system the recognition of ob jects for building semantic 3D maps of the robot's environment. Key words: visual attention, saliency detection, bimodal sensor fusion, 3D laser scanner

  @article{CVIU_2005, abstract = {In this paper, we present a new bimodal attention system for robotic applications capable of processing data from different sensor modes simultaneously. Considering several sensor modalities is an obvious approach to regard a variety of ob ject properties. Nevertheless, conventional att ention systems only regard the processing of camera images. In contrast to these systems, the input data to our system is provided by a bimodal 3D laser scanner, mounted on top of an autonomous mobile robot. In a single 3D scan pass, the scanner yields range as well as reflectance data. Both dat a modes are illumination independent, yielding a robust approach that enables all day operation. Data from both laser modes are fed into our attention system built on principles of one of the standard models of visual attention by Koch & Ullman. The system computes conspicuities of both modes in parallel and fuses them into one saliency map. The focus of attention is directed to the most salient points in this map sequentially. We present results on recorded scans of indoor and outdoor scenes showing the respective advantages of the sensor modalities enabling the mode-specific detectio n of different ob ject properties. Furthermore, we show as an application of the attention system the recognition of ob jects for building semantic 3D maps of the robot's environment. Key words: visual attention, saliency detection, bimodal sensor fusion, 3D laser scanner}, author = {Frintrop, S. and Rome, E. and N{\"u}chter, A. and Surmann, H.}, journal = {Journal Computer Vision and Image Understanding (CVIU), Special Issue on Attention and Performance in Computer Vision}, keywords = {myown}, month = 10, number = {1-2}, pages = {124–151}, title = {A Bimodal Laser-Based Attention System}, volume = 100, year = 2005 }
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  6D SLAM with Approximate Data Association. Nüchter, A.; Lingemann, K.; Hertzberg, J.; Surmann, H. In Proceedings of the 12th IEEE International Conference on Advanced Robotics (ICAR ’05), pp. 242–249. 2005.
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  This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. A fast variant of the iterative closest points (ICP) algorithm registers 3D scans taken by a mobile robot into a common coordinate system and thus provides relocalization. Hereby, data association is reduced to the problem of searching for closest points. Approximation algorithms for this searching, namely, approximate kd-trees and box decomposition trees, are presented and evaluated in this paper. A solution to 6D SLAM that considers all free parameters in the robot pose is built based on 3D scan matching.

  @inproceedings{ICAR2005_2, abstract = {This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. A fast variant of the iterative closest points (ICP) algorithm registers 3D scans taken by a mobile robot into a common coordinate system and thus provides relocalization. Hereby, data association is reduced to the problem of searching for closest points. Approximation algorithms for this searching, namely, approximate kd-trees and box decomposition trees, are presented and evaluated in this paper. A solution to 6D SLAM that considers all free parameters in the robot pose is built based on 3D scan matching.}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Surmann, H.}, booktitle = {Proceedings of the 12th IEEE International Conference on Advanced Robotics (ICAR '05)}, keywords = {imported}, month = {07}, pages = {242–249}, title = {{6D SLAM} with {A}pproximate {D}ata {A}ssociation}, year = 2005 }
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  Robust Object Detection at Regions of Interest with an Application in Ball Recognition. Mitri, S.; Frintrop, S.; Pervölz, K.; Surmann, H.; Nüchter, A. In Proceedings of the IEEE International Conference Robotics and Automation (ICRA ’05), pp. 126–131. Barcelona, Spain, 2005.
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  In this paper, we present a new combination of a biologically inspired attention system (VOCUS – Visual Object detection with a CompUtational attention System) with a robust object detection method. As an application, we built a reliable system for ball recognition in the RoboCup context. Firstly, VOCUS finds regions of interest generating a hypothesis for possible locations of the ball. Secondly, a fast classifier verifies the hypothesis by detecting balls at regions of interest. The combination of both approaches makes the system highly robust and eliminates false detections. Furthermore, the system is quickly adaptable to balls in different scenarios: The complex classifier is universally applicable to balls in every context and the attention system improves the performance by learning scenario-specific features quickly from only a few training examples.

  @inproceedings{ICRA2005, abstract = {In this paper, we present a new combination of a biologically inspired attention system (VOCUS – Visual Object detection with a CompUtational attention System) with a robust object detection method. As an application, we built a reliable system for ball recognition in the RoboCup context. Firstly, VOCUS finds regions of interest generating a hypothesis for possible locations of the ball. Secondly, a fast classifier verifies the hypothesis by detecting balls at regions of interest. The combination of both approaches makes the system highly robust and eliminates false detections. Furthermore, the system is quickly adaptable to balls in different scenarios: The complex classifier is universally applicable to balls in every context and the attention system improves the performance by learning scenario-specific features quickly from only a few training examples.}, address = {Barcelona, Spain}, author = {Mitri, S. and Frintrop, S. and Perv{\"o}lz, K. and Surmann, H. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference Robotics and Automation (ICRA '05)}, keywords = {imported}, month = {04}, pages = {126–131}, title = {{Robust Object Detection at Regions of Interest with an Application in Ball Recognition}}, year = 2005 }
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  Simultaneous Mapping and Localization of Rescue Environments. Surmann, H.; Pervölz, K.; Nüchter, A.; Lingemann, K.; Hertzberg, J.; Hennig, M. In it- Information Technology, 47, pp. 282–291. Oldenbourg press, 2005.
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  @article{it2005, author = {Surmann, H. and Perv{\"o}lz, K. and N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Hennig, M.}, journal = {it- Information Technology}, keywords = {imported}, pages = {282–291}, publisher = {Oldenbourg press}, title = {{Simultaneous Mapping and Localization of Rescue Environments}}, volume = 47, year = 2005 }
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  RoboCupRescue - Robot League Team, Team Deutschland1. Surmann, H.; Lingemann, K.; Nüchter, A.; Hennig, M.; Pervölz, K.; Wulf, O.; Hertzberg, J.; Wagner, B.; Christaller, T. Team Description Paper, Rescue Robot League Competition, Osaka, Japan, 2005.
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  After the second place in RoboCup Rescue 2004, a new version of the mobile robot Kurt3D was developed in our groups during the last year [1]. The key innovation of this system lies in the capability for autonomous or operator-assisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, Kurt3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment e.g. infrared camera and CO2sensor. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of Kurt3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we are confident of managing the rescue robot league competition, too.

  @techreport{TDP2005, abstract = {After the second place in RoboCup Rescue 2004, a new version of the mobile robot Kurt3D was developed in our groups during the last year [1]. The key innovation of this system lies in the capability for autonomous or operator-assisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, Kurt3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment e.g. infrared camera and CO2sensor. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of Kurt3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we are confident of managing the rescue robot league competition, too.}, address = {Osaka, Japan}, author = {Surmann, H. and Lingemann, K. and N{\"u}chter, A. and Hennig, M. and Perv{\"o}lz, K. and Wulf, O. and Hertzberg, J. and Wagner, B. and Christaller, T.}, institution = {Team Description Paper, Rescue Robot League Competition}, keywords = {myown}, month = {07}, title = {{RoboCupRescue - Robot League Team, Team Deutschland1}}, year = 2005 }
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  Accurate Object Localization in 3D Laser Range Scans. Nüchter, A.; Lingemann, K.; Hertzberg, J.; Surmann, H. In Proceedings of the 12th IEEE International Conference on Advanced Robotics (ICAR ’05), pp. 665–672. 2005.
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  This paper presents a novel method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot. Unrestricted objects are learned using classification and regression trees (CARTs) and using an Ada Boost learning procedure. Off-screen rendered depth and reflectance images serve as an input for learning. The performance of the classification is improved by combining both sensor modalities, which are independent from external light. This enables highly accurate, fast and reliable 3D object localization with point matching. Competitive learning is used for evaluating the accuracy of the object localization.

  @inproceedings{ICAR2005_1, abstract = {This paper presents a novel method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot. Unrestricted objects are learned using classification and regression trees (CARTs) and using an Ada Boost learning procedure. Off-screen rendered depth and reflectance images serve as an input for learning. The performance of the classification is improved by combining both sensor modalities, which are independent from external light. This enables highly accurate, fast and reliable 3D object localization with point matching. Competitive learning is used for evaluating the accuracy of the object localization.}, author = {N{\"u}chter, A. and Lingemann, K. and Hertzberg, J. and Surmann, H.}, booktitle = {Proceedings of the 12th IEEE International Conference on Advanced Robotics (ICAR '05)}, keywords = {imported}, month = {07}, pages = {665–672}, title = {{A}ccurate {O}bject {L}ocalization in {3D} {L}aser {R}ange {S}cans}, year = 2005 }

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  6D SLAM A Preliminary Report on Closing the Loop in Six Dimensions. Surmann, H.; Nüchter, A.; Lingemann, K.; Hertzberg, J. In Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV ’04). Lisbon, Portugal, 2004.
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  To create 3D volumetric maps of scenes with autonomous mobile robots it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points (ICP) algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using closing loop detection and a global relaxation. Keywords: autonomous mobile robots, 3D laser scanner, 3D scan matching, simultaneous localization and mapping (SLAM), closing loop.

  @inproceedings{IAV2004, abstract = {To create 3D volumetric maps of scenes with autonomous mobile robots it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points (ICP) algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using closing loop detection and a global relaxation. Keywords: autonomous mobile robots, 3D laser scanner, 3D scan matching, simultaneous localization and mapping (SLAM), closing loop.}, address = {Lisbon, Portugal}, author = {Surmann, H. and N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the 5th IFAC Symposium on Intelligent Autonomous Vehicles (IAV '04)}, keywords = {myown}, month = {07}, title = {{6D SLAM} {A} {P}reliminary {R}eport on {C}losing the {L}oop in {S}ix {D}imensions}, year = 2004 }
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  Indoor and Outdoor Localization for Fast Mobile Robots. Lingemann, K.; Surmann, H.; Nüchter, A.; Hertzberg, J. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’04), pp. 2185–2190. Sendai, Japan, 2004.
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  This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computational time, being 33 times faster than real time. The efficiency is achieved by a closed form solution for the matching of two lasers scans, the use of natural landmarks and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.

  @inproceedings{IROS2004, abstract = {This paper describes a novel, laser-based approach for tracking the pose of a high-speed mobile robot. The algorithm is outstanding in terms of accuracy and computational time, being 33 times faster than real time. The efficiency is achieved by a closed form solution for the matching of two lasers scans, the use of natural landmarks and fast linear filters. The implemented algorithm is evaluated with the high-speed robot Kurt3D (4 m/s), and compared to standard scan matching methods in indoor and outdoor environments.}, address = {Sendai, Japan}, author = {Lingemann, K. and Surmann, H. and N{\"u}chter, A. and Hertzberg, J.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '04)}, keywords = {imported}, month = {09}, pages = {2185–2190}, title = {{I}ndoor and {O}utdoor {L}ocalization for {F}ast {M}obile {R}obots}, year = 2004 }
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  Searching with an Autonomous Robot. Fekete, S.; Klein, R.; Nüchter, A. In Proccedings of the 20th ACM Annual Symposium on Computational Geometry (SoCG ’04), pp. 449–450. New York, USA, 2004.
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  We demonstrate how one of the classical areas of computational geometry has reached practical application, which in turn gives rise to new, fascinating geometric problems. In particular, we discuss the problem of developing a good online strategy for an autonomous mobile robot to locate an object that is hidden behind a corner or door.

  @inproceedings{SOCG2004, abstract = {We demonstrate how one of the classical areas of computational geometry has reached practical application, which in turn gives rise to new, fascinating geometric problems. In particular, we discuss the problem of developing a good online strategy for an autonomous mobile robot to locate an object that is hidden behind a corner or door.}, address = {New York, USA}, author = {Fekete, S. and Klein, R. and N{\"u}chter, A.}, booktitle = {Proccedings of the 20th ACM Annual Symposium on Computational Geometry (SoCG '04)}, keywords = {myown}, month = {06}, pages = {449–450}, title = {{Searching with an Autonomous Robot}}, year = 2004 }
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  Focussing Object Recognition on Regions of Interest. Frintrop, S.; Rome, E.; Nüchter, A.; Surmann, H. In Proceedings of the 7. Tübingen Perception Conference (TWK ’04), H. Bülthoff, H. A. Mallot, R. Ulrich, F. A. Wichmann (eds.), p. 67. Tübingen, Germany, 2004.
  • [ BibTeX ]
  @inproceedings{TWK2004, address = {T{\"u}bingen, Germany}, author = {Frintrop, S. and Rome, E. and N{\"u}chter, A. and Surmann, H.}, booktitle = {Proceedings of the 7. T{\"u}bingen Perception Conference (TWK '04)}, editor = {B{\"u}lthoff, H. and Mallot, H. A. and Ulrich, R. and Wichmann, F. A.}, keywords = {imported}, month = {02}, pages = 67, title = {{Focussing Object Recognition on Regions of Interest}}, year = 2004 }
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  Online Searching with an Autononmous Robot. Fekete, S.; Klein, R.; Nüchter, A. In Algorithmic Foundations of Robotics VI, STAR 17 (Proceedings of the 6th International Workshop on the Algorithmic Foundations of Robotics (WAFR ’04)), Vol. 17 of Springer Tracts in Advanced Robotics, pp. 139–154. Zeist/Utrecht, The Netherlands, 2004.
  • [ Abstract ]
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  We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning tra jectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.

  @inproceedings{WAFR2004, abstract = {We discuss online strategies for visibility-based searching for an ob ject hidden behind a corner, using Kurt3D, a real autonomous mobile robot. This task is closely related to a number of well-studied problems. Our robot uses a threedimensional laser scanner in a stop, scan, plan, go fashion for building a virtual three-dimensional environment. Besides planning tra jectories and avoiding obstacles, Kurt3D is capable of identifying objects like a chair. We derive a practically useful and asymptotically optimal strategy that guarantees a competitive ratio of 2, which differs remarkably from the well-studied scenario without the need of stopping for surveying the environment. Our strategy is used by Kurt3D, documented in a separate video.}, address = {Zeist/Utrecht, The Netherlands}, author = {Fekete, S. and Klein, R. and N{\"u}chter, A.}, booktitle = {Algorithmic Foundations of Robotics VI, STAR 17 (Proceedings of the 6th International Workshop on the Algorithmic Foundations of Robotics (WAFR '04))}, keywords = {myown}, month = {07}, pages = {139–154}, series = {Springer Tracts in Advanced Robotics}, title = {{Online Searching with an Autononmous Robot}}, volume = 17, year = 2004 }
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  Ultra-fast Holographic Recording and Automatic 3D Scan Matching of Living Human Faces. Giel, D.; Frey, S.; Thelen, A.; Bongartz, J.; Hering, P.; Nüchter, A.; Surmann, H.; Lingemann, K.; Hertzberg, J. In Proceedings of the Scientific Workshop Medical Robotics, Navigation and Visualization (MRNV ’04). Remagen, Germany, 2004.
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  3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analysis of the real image yields a surface relief of the patient. To generate a complete 360◦ patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm is used to compute such a minimum. We propose a new fast approximation based on kD trees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.

  @inproceedings{MRNV2004, abstract = {3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analysis of the real image yields a surface relief of the patient. To generate a complete 360◦ patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm is used to compute such a minimum. We propose a new fast approximation based on kD trees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.}, address = {Remagen, Germany}, author = {Giel, D. and Frey, S. and Thelen, A. and Bongartz, J. and Hering, P. and N\"{u}chter, A. and Surmann, H. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the Scientific Workshop Medical Robotics, Navigation and Visualization (MRNV '04)}, keywords = {myown}, month = {03}, title = {{Ultra-fast Holographic Recording and Automatic 3D Scan Matching of Living Human Faces}}, year = 2004 }
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  Fast Color-Independent Ball Detection for Mobile Robots. Mitri, S.; Pervölz, K.; Surmann, H.; Nüchter, A. In Proceedings of the IEEE International Conference Mechatronics and Robotics 2004 (MechRob ’04), pp. 900–905. Aachen, Germany, 2004.
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  This paper presents a novel scheme for fast color invariant ball detection in the RoboCup context. Edge filtered camera images serve as an input for an Ada Boost learning procedure that constructs a cascade of classification and regression trees (CARTs). Our system is capable to detect different soccer balls in the RoboCup and other environments. The resulting approach for object classification is real-time capable and reliable.

  @inproceedings{MECHROB2004, abstract = {This paper presents a novel scheme for fast color invariant ball detection in the RoboCup context. Edge filtered camera images serve as an input for an Ada Boost learning procedure that constructs a cascade of classification and regression trees (CARTs). Our system is capable to detect different soccer balls in the RoboCup and other environments. The resulting approach for object classification is real-time capable and reliable.}, address = {Aachen, Germany}, author = {Mitri, S. and Perv{\"o}lz, K. and Surmann, H. and N{\"u}chter, A.}, booktitle = {Proceedings of the IEEE International Conference Mechatronics and Robotics 2004 (MechRob '04)}, keywords = {imported}, month = {09}, pages = {900–905}, title = {{Fast Color-Independent Ball Detection for Mobile Robots}}, year = 2004 }
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  6D SLAM with an Application in Autonomous Mine Mapping. Nüchter, A.; Surmann, H.; Lingemann, K.; Hertzberg, J.; Thrun, S. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA ’04), pp. 1998–2003. New Orleans, USA, 2004.
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  To create with an autonomous mobile robot a 3D volumetric map of a scene it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using a global relaxation. The algorithms have been tested with 3D scans taken in the Mathies mine, Pittsburgh, PA. Abandoned mines pose significant problems to society, yet a large fraction of them lack accurate 3D maps.

  @inproceedings{ICRA2004, abstract = {To create with an autonomous mobile robot a 3D volumetric map of a scene it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. Robot motion on natural surfaces has to cope with yaw, pitch and roll angles, turning pose estimation into a problem in six mathematical dimensions. A fast variant of the Iterative Closest Points algorithm registers the 3D scans in a common coordinate system and relocalizes the robot. Finally, consistent 3D maps are generated using a global relaxation. The algorithms have been tested with 3D scans taken in the Mathies mine, Pittsburgh, PA. Abandoned mines pose significant problems to society, yet a large fraction of them lack accurate 3D maps.}, address = {New Orleans, USA}, author = {N{\"u}chter, A. and Surmann, H. and Lingemann, K. and Hertzberg, J. and Thrun, S.}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '04)}, keywords = {imported}, month = {04}, pages = {1998–2003}, title = {{6D SLAM} with an {A}pplication in {A}utonomous {M}ine {M}apping}, year = 2004 }
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  Automatic Reconstruction of Colored 3D Models. Pervölz, K.; Nüchter, A.; Surmann, H.; Hertzberg, J. In Proceedings of Robotik 2004, VDI-Berichte 1841, of VDI-Berichte 1841, pp. 215–222. Munich, Germany, 2004.
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  A basic issue of mobile robotics is the automatic generation of environment maps. This paper presents novel results for the reconstruction of textured 3D maps with an autonomous mobile robot, a 3D laser range finder and two pan-tilt color cameras. Building 3D maps involves a number of fundamental scientific issues. This paper adresses the issue of how to fuse the geometry data of the 3D laser range finder with camera images. The proposed algorithm allows to texturize geometrical 3D scenes-models.

  @inproceedings{ROBOTIK2004, abstract = {A basic issue of mobile robotics is the automatic generation of environment maps. This paper presents novel results for the reconstruction of textured 3D maps with an autonomous mobile robot, a 3D laser range finder and two pan-tilt color cameras. Building 3D maps involves a number of fundamental scientific issues. This paper adresses the issue of how to fuse the geometry data of the 3D laser range finder with camera images. The proposed algorithm allows to texturize geometrical 3D scenes-models.}, address = {Munich, Germany}, author = {Perv{\"o}lz, K. and N{\"u}chter, A. and Surmann, H. and Hertzberg, J.}, booktitle = {Proceedings of Robotik 2004, VDI-Berichte 1841}, keywords = {imported}, month = {06}, pages = {215–222}, series = {VDI-Berichte 1841}, title = {{Automatic Reconstruction of Colored 3D Models}}, year = 2004 }
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  Visual Attention for Object Recognition in Spatial 3D Data. Frintrop, S.; Nüchter, A.; Surmann, H. In Proceedings of 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV ’04), of Revised Selected Papers Series: Lecture Notes in Computer Science, Vol. 3368, L. Paletta, J. K. Tsotsos, E. Rome, G. Humphreys (eds.). Prague, Czech Republic, 2004.
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  In this paper, we present a new recognition system for the fast detection and classification of objects in spatial 3D data. The system consists of two main components: A biologically motivated attention system and a fast classifier. Input is provided by a 3D laser scanner, mounted on an autonomous mobile robot, that acquires illumination independent range and reflectance data. These are rendered into images and fed into the attention system that detects regions of potential interest. The classifier is applied only to a region of interest, yielding a significantly faster classification that requires only 30\% of the time of an exhaustive search. Furthermore, both the attention and the classification system benefit from the fusion of the bi-modal data, considering more object properties for the detection of regions of interest and a lower false detection rate in classification.

  @inproceedings{WAPCV2004, abstract = {In this paper, we present a new recognition system for the fast detection and classification of objects in spatial 3D data. The system consists of two main components: A biologically motivated attention system and a fast classifier. Input is provided by a 3D laser scanner, mounted on an autonomous mobile robot, that acquires illumination independent range and reflectance data. These are rendered into images and fed into the attention system that detects regions of potential interest. The classifier is applied only to a region of interest, yielding a significantly faster classification that requires only 30\% of the time of an exhaustive search. Furthermore, both the attention and the classification system benefit from the fusion of the bi-modal data, considering more object properties for the detection of regions of interest and a lower false detection rate in classification.}, address = {Prague, Czech Republic}, author = {Frintrop, S. and N{\"u}chter, A. and Surmann, H.}, booktitle = {Proceedings of 2nd International Workshop on Attention and Performance in Computational Vision (WAPCV '04)}, editor = {Paletta, L. and Tsotsos, J. K. and Rome, E. and Humphreys, G.}, keywords = {myown}, month = {05}, series = {Revised Selected Papers Series: Lecture Notes in Computer Science, Vol. 3368}, title = {{Visual Attention for Object Recognition in Spatial 3D Data}}, year = 2004 }
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  Saliency-based Object Recognition in 3D Data. Frintrop, S.; Nüchter, A.; Surmann, H.; Hertzberg, J. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS ’04), pp. 2167–2172. Sendai, Japan, 2004.
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  This paper presents a robust and real-time capable recognition system for the fast detection and classification of objects in spatial 3D data. Depth and reflection data from a 3D laser scanner are rendered into images and fed into a saliency-based visual attention system that detects regions of potential interest. Only these regions are examined by a fast classifier. The time saving of classifying objects in salient regions rather than in complete images is linear with the number of trained object classes. Robustness is achieved by the fusion of the bi-modal scanner data; in contrast to camera images, this data is completely illumination independent. The recognition system is trained for two different object classes and evaluated on real indoor data.

  @inproceedings{IROS2004_1, abstract = {This paper presents a robust and real-time capable recognition system for the fast detection and classification of objects in spatial 3D data. Depth and reflection data from a 3D laser scanner are rendered into images and fed into a saliency-based visual attention system that detects regions of potential interest. Only these regions are examined by a fast classifier. The time saving of classifying objects in salient regions rather than in complete images is linear with the number of trained object classes. Robustness is achieved by the fusion of the bi-modal scanner data; in contrast to camera images, this data is completely illumination independent. The recognition system is trained for two different object classes and evaluated on real indoor data.}, address = {Sendai, Japan}, author = {Frintrop, S. and N{\"u}chter, A. and Surmann, H. and Hertzberg, J.}, booktitle = {Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '04)}, keywords = {myown}, month = {09}, pages = {2167–2172}, title = {{S}aliency-based {O}bject {R}ecognition in {3D} {D}ata}, year = 2004 }
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  Automatic Classification of Objects in 3D Laser Range Scans. Nüchter, A.; Surmann, H.; Hertzberg, J. In Proceedings of the 8th Conference on Intelligent Autonomous Systems (IAS ’04), pp. 963–970. Amsterdam, The Netherlands, 2004.
  • [ Abstract ]
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  3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analys is of the real image yields a surface relief of the patient. To generate a complete 360 patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm2 is used to compute such a minimum. We propose a new fast approximation based on kDtrees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.

  @inproceedings{IAS2004, abstract = {3D models of the skin surface of patients are created by ultra-fast holography and automatic scan matching of synchronously recorded holograms. By recording with a pulsed laser and continuous-wave optical reconstruction of the holographic real image, motion artifacts are eliminated. Focal analys is of the real image yields a surface relief of the patient. To generate a complete 360 patient model, several synchronously recorded reliefs are registered by automatic scan matching. We find the transformation consisting of a rotation and a translation that minimizes a cost function containing the Euclidian distances between points pairs from two surface relief maps. A variant of the ICP (Iterative Closest Points) algorithm2 is used to compute such a minimum. We propose a new fast approximation based on kDtrees for the problem of creating the closest point pairs on which the ICP algorithm spends most of its time.}, address = {Amsterdam, The Netherlands}, author = {N{\"u}chter, A. and Surmann, H. and Hertzberg, J.}, booktitle = {Proceedings of the 8th Conference on Intelligent Autonomous Systems (IAS '04)}, keywords = {imported}, month = {03}, pages = {963–970}, title = {{A}utomatic {C}lassification of {O}bjects in {3D} {L}aser {R}ange {S}cans}, year = 2004 }
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  RoboCupRescue - Robot League Team, Team Kurt3D. Surmann, H.; Worst, R.; Hennig, M.; Lingemann, K.; Nüchter, A.; Pervölz, K.; Tiruchinapalli, K. Raj; Christaller, T.; Hertzberg, J. Team Description Paper, Rescue Robot League Competition, Portugal, 2004.
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  A mobile robot named KURT3D was developed at the Fraunhofer Institute for Autonomous Intelligent Systems during the last three years. The key innovation of this system lies in the capability for autonomous or operatorassisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, KURT3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of KURT3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we a reconfident of managing the rescue robot league competition, too.

  @techreport{TDP2004, abstract = {A mobile robot named KURT3D was developed at the Fraunhofer Institute for Autonomous Intelligent Systems during the last three years. The key innovation of this system lies in the capability for autonomous or operatorassisted 6D SLAM (simultaneous localization and mapping) and 3D map generation of natural scenes. Hence, KURT3D already meets the basic requirement regarding urban search and rescue. For the rescue robot league competition, it is additionally configured with dedicated state-of-the-art equipment. The robot and the operator station are rather compact and easy to set up. The operator uses a joystick as a remote control for the robot and can watch a live video of the scene where the robot drives. Data are transmitted via wireless LAN. A 3D laser scanner, which is mounted on an outdoor variant of KURT3D, is used as the main sensor for map generation as well as for navigation and localization. The whole system has been used with a proven record of success for different tasks of map building, so that we a reconfident of managing the rescue robot league competition, too.}, address = {Portugal}, author = {Surmann, H. and Worst, R. and Hennig, M. and Lingemann, K. and N{\"u}chter, A. and Perv{\"o}lz, K. and Tiruchinapalli, K. Raj and Christaller, T. and Hertzberg, J.}, institution = {Team Description Paper, Rescue Robot League Competition}, keywords = {myown}, month = {07}, title = {{RoboCupRescue - Robot League Team, Team Kurt3D}}, year = 2004 }

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  Schnelle Visualisierung von Radialen 3D-Laserscans. Nüchter, A. In Proceedings of the 5. Fachwissenschaftlicher Informatikkongress - Informatiktage 2003, pp. 243–246. Bad Schussenried, Germany, 2003.
  • [ BibTeX ]
  @inproceedings{IT2003, address = {Bad Schussenried, Germany}, author = {N{\"u}chter, A.}, booktitle = {Proceedings of the 5. Fachwissenschaftlicher Informatikkongress - Informatiktage 2003}, keywords = {imported}, month = 11, pages = {243–246}, title = {{Schnelle Visualisierung von Radialen 3D-Laserscans}}, year = 2003 }
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  Autonomous Mobile Robots for 3D Digitalization of Indoor Environments. Surmann, H.; Nüchter, A.; Hertzberg, J. In of GMD Report 147. GMD - Forschungszentrum Informationstechnik GmbH, Sankt Augustin, Germany, 2003.
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  @book{REPORT2003, address = {Sankt Augustin, Germany}, author = {Surmann, H. and N{\"u}chter, A. and Hertzberg, J.}, keywords = {imported}, publisher = {GMD - Forschungszentrum Informationstechnik GmbH}, series = {GMD Report 147}, title = {{Autonomous Mobile Robots for 3D Digitalization of Indoor Environments}}, year = 2003 }
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  An Attentive, Multi-modal Laser Eye. Frintrop, S.; Rome, E.; Nüchter, A.; Surmann, H. In Proceedings of the third International Conference on Computer Vision Systems (ICVS ’03), pp. 202–211. Graz, Austria, 2003.
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  In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interes t in an arbitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast ma jority of the prima ry attended locations pointed to scene ob jects of potential interest for navigation and ob ject detection tasks. Moreover, both sensor modalities c omplement each other, resulting in a greater variety of points of interest than one modality alone can provide.

  @inproceedings{ICVS2003, abstract = {In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interes t in an arbitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast ma jority of the prima ry attended locations pointed to scene ob jects of potential interest for navigation and ob ject detection tasks. Moreover, both sensor modalities c omplement each other, resulting in a greater variety of points of interest than one modality alone can provide.}, address = {Graz, Austria}, author = {Frintrop, S. and Rome, E. and N{\"u}chter, A. and Surmann, H.}, booktitle = {Proceedings of the third International Conference on Computer Vision Systems (ICVS '03)}, keywords = {imported}, month = {04}, pages = {202–211}, title = {{An Attentive, Multi-modal Laser Eye}}, year = 2003 }
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  Visuelle Aufmerksamkeitsmechanismen auf bimodalen Laserdaten. Frintrop, S.; Rome, E.; Nüchter, A.; Surmann, H. In Beiträge zur 6. Tübinger Wahrnehmungskonferenz (TWK ’03), p. 100. Tübingen, Germnay, 2003.
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  @inproceedings{TWK2003, address = {T{\"u}bingen, Germnay}, author = {Frintrop, S. and Rome, E. and N{\"u}chter, A. and Surmann, H.}, booktitle = {Beitr{\"a}ge zur 6. T{\"u}binger Wahrnehmungskonferenz (TWK '03)}, keywords = {imported}, month = {02}, pages = 100, title = {{Visuelle Aufmerksamkeitsmechanismen auf bimodalen Laserdaten}}, year = 2003 }
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  Semantic Scene Analysis of Scanned 3D Indoor Environments. Nüchter, A.; Surmann, H.; Lingemann, K.; Hertzberg, J. In Proceedings of the of the 8th International Fall Workshop Vision, Modeling, and Visualization (VMV ’03), pp. 215–222. Munich, Germany, 2003.
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  Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new method that transforms a 3D volumetric model, acquired by a mobile robot equipped with a 3D laser scanner, into a very precise compact 3D map and generates semantic descriptions. The scanned 3D scene is matched against a coarse semantic description of general indoor environments. The matching is done by a Prolog program compiled from the scanned 3D scene and combined with clauses from the coarse semantic description. The generated scene specific knowledge produced by the unification in the Prolog program is used to refine the 3D model.

  @inproceedings{VMV2003, abstract = {Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new method that transforms a 3D volumetric model, acquired by a mobile robot equipped with a 3D laser scanner, into a very precise compact 3D map and generates semantic descriptions. The scanned 3D scene is matched against a coarse semantic description of general indoor environments. The matching is done by a Prolog program compiled from the scanned 3D scene and combined with clauses from the coarse semantic description. The generated scene specific knowledge produced by the unification in the Prolog program is used to refine the 3D model.}, address = {Munich, Germany}, author = {N{\"u}chter, A. and Surmann, H. and Lingemann, K. and Hertzberg, J.}, booktitle = {Proceedings of the of the 8th International Fall Workshop Vision, Modeling, and Visualization (VMV '03)}, keywords = {imported}, month = 11, pages = {215–222}, title = {{S}emantic {S}cene {A}nalysis of {S}canned {3D} {I}ndoor {E}nvironments}, year = 2003 }
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  An autonomous mobile robot with a 3D laser range finder for 3D exploration and digitalization of indoor environments. Surmann, H.; Nüchter, A.; Hertzberg, J. In Journal Robotics and Autonomous Systems (JRAS), 45(3--4), pp. 181–198. 2003.
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  Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presen ts an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and three elaborated software modules. The first module, a fast variant of the Iterative Closest Points algorithm, registers the 3D scans in a common coordinate system and relocalizes the robot. The second module, a next best view planner, computes the next nominal pose based on the acquired 3D data while avoiding complicated obstacles. The third module, a closed-loop and globally stable motor controller, navigates the mobile robot to a nominal pose on the base of odometry and avoids collisions with dynamical obstacles. The 3D laser range finder acquires a 3D scan at this pose. The proposed method allows one to digitalize large indoor environments fast and reliably without any intervention and solves the SLAM problem. The results of two 3D digitalization experiments are presented using a fast octree-based visualization method.

  @article{RAAS2003, abstract = {Digital 3D models of the environment are needed in rescue and inspection robotics, facility managements and architecture. This paper presen ts an automatic system for gaging and digitalization of 3D indoor environments. It consists of an autonomous mobile robot, a reliable 3D laser range finder and three elaborated software modules. The first module, a fast variant of the Iterative Closest Points algorithm, registers the 3D scans in a common coordinate system and relocalizes the robot. The second module, a next best view planner, computes the next nominal pose based on the acquired 3D data while avoiding complicated obstacles. The third module, a closed-loop and globally stable motor controller, navigates the mobile robot to a nominal pose on the base of odometry and avoids collisions with dynamical obstacles. The 3D laser range finder acquires a 3D scan at this pose. The proposed method allows one to digitalize large indoor environments fast and reliably without any intervention and solves the SLAM problem. The results of two 3D digitalization experiments are presented using a fast octree-based visualization method.}, author = {Surmann, H. and N{\"u}chter, A. and Hertzberg, J.}, journal = {Journal Robotics and Autonomous Systems (JRAS)}, keywords = {imported}, month = 12, number = {3–4}, pages = {181–198}, title = {{A}n autonomous mobile robot with a {3D} laser range finder for {3D} exploration and digitalization of indoor environments}, volume = 45, year = 2003 }
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  Planning Robot Motion for 3D Digitalization of Indoor Environments. Nüchter, A.; Surmann, H.; Hertzberg, J. In Proceedings of the 11th IEEE International Conference on Advanced Robotics (ICAR ’03), pp. 222–227. Coimbra, Portugal, 2003.
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  3D digitalization of environments without occlusions requires multiple 3D scans. Autonomous mobile robots equipped with a 3D laser scanner are wel l suited for the gaging task. They need an efficient exploration scheme for the digitalization. We present a new approach for planning the next scan pose as well as the robot motion. Our approach calculates a collision free trajectory regarding complicated objects, e.g., with jutting out edges. A closed loop and global ly stable motor control ler navigates the mobile robot. The results of a 3D digitalization experiment in the main hall of castle Birlinghoven is presented.

  @inproceedings{ICAR2003, abstract = {3D digitalization of environments without occlusions requires multiple 3D scans. Autonomous mobile robots equipped with a 3D laser scanner are wel l suited for the gaging task. They need an efficient exploration scheme for the digitalization. We present a new approach for planning the next scan pose as well as the robot motion. Our approach calculates a collision free trajectory regarding complicated objects, e.g., with jutting out edges. A closed loop and global ly stable motor control ler navigates the mobile robot. The results of a 3D digitalization experiment in the main hall of castle Birlinghoven is presented.}, address = {Coimbra, Portugal}, author = {N{\"u}chter, A. and Surmann, H. and Hertzberg, J.}, booktitle = {Proceedings of the 11th IEEE International Conference on Advanced Robotics (ICAR '03)}, keywords = {imported}, month = {06}, pages = {222–227}, title = {{P}lanning {R}obot {M}otion for {3D} {D}igitalization of {I}ndoor {E}nvironments}, year = 2003 }
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  Autonome Exploration und 3D-Modellierung der Umgebung eines Roboters. Nüchter, A. In Tagungsband zum 4. Fachwissenschaftlichen Informatikkongress - Informatiktage 2002, pp. 64–68. Bad Schussenried, Germany, 2003.
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  Autonome mobile Roboter müssen in der Lage sein, sicher durch ihre Umgebung zu navigieren, um anwendungsspezifische Aufgaben ausführen zu können. Gelingen kann dies nur durch den Einsatz von 3D-Sensoren und 3D-Karten. Daher ist die automatische und schnelle 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten mölich macht. Die vorliegende Arbeit untersucht und evaluiert die zur autonome n 3D-Kartenerstellung notwendigen Algorithmen mit Hilfe des AIS 3D-Laserscanners, der sich auf einer geeigneten Roboterplattform befindet. Das entwickelte System ermöglicht das berhrungslose Abtasten der gesamten Umgebung. Dafür werden mehrere 3D-Scans zu einer konsistenten Szene zusammengefügt sowie Scanpositionen generiert.

  @inproceedings{IT2002, abstract = {Autonome mobile Roboter müssen in der Lage sein, sicher durch ihre Umgebung zu navigieren, um anwendungsspezifische Aufgaben ausführen zu können. Gelingen kann dies nur durch den Einsatz von 3D-Sensoren und 3D-Karten. Daher ist die automatische und schnelle 3D-Modellierung der Umgebung eine wichtige Fragestellung in der Robotik. 3D-Laserscanner sind eine junge Technologie, die die Erfassung räumlicher Daten revolutioniert und Robotern das dreidimensionale Abtasten von Objekten mölich macht. Die vorliegende Arbeit untersucht und evaluiert die zur autonome n 3D-Kartenerstellung notwendigen Algorithmen mit Hilfe des AIS 3D-Laserscanners, der sich auf einer geeigneten Roboterplattform befindet. Das entwickelte System ermöglicht das berhrungslose Abtasten der gesamten Umgebung. Dafür werden mehrere 3D-Scans zu einer konsistenten Szene zusammengefügt sowie Scanpositionen generiert.}, address = {Bad Schussenried, Germany}, author = {N{\"u}chter, A.}, booktitle = {Tagungsband zum 4. Fachwissenschaftlichen Informatikkongress - Informatiktage 2002}, keywords = {myown}, month = 11, pages = {64–68}, title = {{Autonome Exploration und 3D-Modellierung der Umgebung eines Roboters}}, year = 2003 }
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  Kurt3D - An Autonomous Mobile Robot for Modeling the World in 3D. Surmann, H.; Nüchter, A.; Lingemann, K.; Hertzberg, J. In ERCIM NEWS, 55, pp. 24–25. 2003.
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  @article{ERCIM, author = {Surmann, H. and N{\"u}chter, A. and Lingemann, K. and Hertzberg, J.}, journal = {ERCIM NEWS}, keywords = {imported}, month = 10, pages = {24–25}, title = {{Kurt3D - An Autonomous Mobile Robot for Modeling the World in 3D}}, volume = 55, year = 2003 }
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  Consistent 3D Model Construction with Autonomous Mobile Robots. Nüchter, A.; Surmann, H.; Lingemann, K.; Hertzberg, J. In KI 2003: Advances in Artificial Intelligence. 26th Annual German Conference on AI, Proceedings Springer LNAI vol. 2821, pp. 550–564. Hamburg, Germany, 2003.
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  Digital 3D models of the environment are needed in facility management, architecture, rescue and inspection robotics. To create 3D volumet ric models of scenes, rooms or buildings, it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper presen ts a system, composed of a fast and robust, autonomous mobile robot, a precise, cost effective, high quality 3D laser scanner, and reliable scan mat ching algorithms for measuring and reconstructing environments, capable of matching two 3D scans within a fraction of a second. The proposed new sof tware modules for scan matching are fast variants of the iterative closest point algorithm (ICP) for consistent alignment. Two applications are presented: First, the reconstruction of an office environment, second, the fitting of sewer pipes into 3D data to detect deviations from the spatial geometry.

  @inproceedings{KI2003, abstract = {Digital 3D models of the environment are needed in facility management, architecture, rescue and inspection robotics. To create 3D volumet ric models of scenes, rooms or buildings, it is necessary to gage several 3D scans and to merge them into one consistent 3D model. This paper presen ts a system, composed of a fast and robust, autonomous mobile robot, a precise, cost effective, high quality 3D laser scanner, and reliable scan mat ching algorithms for measuring and reconstructing environments, capable of matching two 3D scans within a fraction of a second. The proposed new sof tware modules for scan matching are fast variants of the iterative closest point algorithm (ICP) for consistent alignment. Two applications are presented: First, the reconstruction of an office environment, second, the fitting of sewer pipes into 3D data to detect deviations from the spatial geometry.}, address = {Hamburg, Germany}, author = {N{\"u}chter, A. and Surmann, H. and Lingemann, K. and Hertzberg, J.}, booktitle = {KI 2003: Advances in Artificial Intelligence. 26th Annual German Conference on AI, Proceedings Springer LNAI vol. 2821}, keywords = {myown}, month = {09}, pages = {550–564}, title = {{C}onsistent {3D} {M}odel {C}onstruction with {A}utonomous {M}obile {R}obots}, year = 2003 }
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  Automatic Model Refinement for 3D Reconstruction with Mobile Robots. Nüchter, A.; Surmann, H.; Hertzberg, J. In Proceedings of the 4th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM ’03), pp. 394–401. Banff, Canada, 2003.
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  Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new algorithm that transforms a 3D volumetric model into a very precise compact 3D map and generates semantic descri ptions. Our system is composed of a robust, autonomous mobile robot for the automatic data acquisition and a precise, cost effective, high quality 3 D laser scanner to gage indoor environments. The reconstruction method consists of reliable scan matching and feature detection algorithms. The 3D scene is matched against a coarse semantic description of general indoor environments and the generated knowledge is used to refine the 3D model.

  @inproceedings{3DIM2003, abstract = {Precise digital 3D models of indoor environments are needed in several applications, e.g., facility management, architecture, rescue and inspection robotics. This paper presents a new algorithm that transforms a 3D volumetric model into a very precise compact 3D map and generates semantic descri ptions. Our system is composed of a robust, autonomous mobile robot for the automatic data acquisition and a precise, cost effective, high quality 3 D laser scanner to gage indoor environments. The reconstruction method consists of reliable scan matching and feature detection algorithms. The 3D scene is matched against a coarse semantic description of general indoor environments and the generated knowledge is used to refine the 3D model.}, address = {Banff, Canada}, author = {N{\"u}chter, A. and Surmann, H. and Hertzberg, J.}, booktitle = {Proceedings of the 4th IEEE International Conference on Recent Advances in 3D Digital Imaging and Modeling (3DIM '03)}, keywords = {imported}, month = 10, pages = {394–401}, title = {{A}utomatic {M}odel {R}efinement for {3D} {R}econstruction with {M}obile {R}obots}, year = 2003 }
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  Applying Attentional Mechanisms to Bi-modal 3D Laser Data. Frintrop, S.; Rome, E.; Nüchter, A.; Surmann, H. In Proecceings of the International Workshop on Attention and Performance in Computer Vision (WAPCV ’03), pp. 25–30. Graz, Austria, 2003.
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  In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interest in an ar bitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast majority of the primary attended l ocations pointed to scene objects of potential i nterest for navigation and object detection tasks. Moreover, both sensor modalities complement each other, resulting in a greater variety of points of interest than one modality alone can provide.

  @inproceedings{WAPCV2003, abstract = {In this paper we present experimental results on a novel application of visual attention mechanisms for the selection of points of interest in an ar bitrary scene. The imaging sensor used is a multi-modal 3D laser scanner. In a single 3D scan pass, it is capable of providing range data as well as a gray-scale intensity image. The scanner is mounted on top of an autonomous mobile robot and serves control purposes. We present results achieved by applying the visual attention system of Itti et al. [8] to recorded scans of indoor and outdoor scenes. The vast majority of the primary attended l ocations pointed to scene objects of potential i nterest for navigation and object detection tasks. Moreover, both sensor modalities complement each other, resulting in a greater variety of points of interest than one modality alone can provide.}, address = {Graz, Austria}, author = {Frintrop, S. and Rome, E. and N{\"u}chter, A. and Surmann, H.}, booktitle = {Proecceings of the International Workshop on Attention and Performance in Computer Vision (WAPCV '03)}, keywords = {imported}, month = {04}, pages = {25–30}, title = {{Applying Attentional Mechanisms to Bi-modal 3D Laser Data}}, year = 2003 }

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  Autonome Exploration und Modellierung von 3D-Umgebungen. Nüchter, A. In of GMD Report 157. GMD - Forschungszentrum Informationstechnik GmbH, Sankt Augustin, Germany, 2002.
  • [ BibTeX ]
  @book{REPORT2002, address = {Sankt Augustin, Germany}, author = {N{\"u}chter, A.}, keywords = {imported}, month = {07}, publisher = {GMD - Forschungszentrum Informationstechnik GmbH}, series = {GMD Report 157}, title = {{Autonome Exploration und Modellierung von 3D-Umgebungen}}, year = 2002 }
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  Autonome Exploration und Modellierung von 3D-Umgebungen. Technical Report (Master thesis), . Nüchter, A. Master thesis. Universität Bonn, 2002, July.
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  @mastersthesis{DIPLOM2002, author = {N{\"u}chter, A.}, keywords = {imported}, month = {07}, school = {Universit{\"a}t Bonn}, title = {{Autonome Exploration und Modellierung von 3D-Umgebungen}}, year = 2002 }

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  Aufbau eines 3D--Laserscanners für autonome mobile Roboter, GMD Report 126. Surmann, H.; Lingemann, K.; Nüchter, A.; Hertzberg, J. In of GMD-Report 126. GMD - Forschungszentrum Informationstechnik GmbH, Sankt Augustin, 2001.
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  @book{REPORT2001, address = {Sankt Augustin}, author = {Surmann, H. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J.}, keywords = {imported}, month = {03}, publisher = {GMD - Forschungszentrum Informationstechnik GmbH}, series = {GMD-Report 126}, title = {Aufbau eines 3D–Laserscanners f{\"u}r autonome mobile Roboter, GMD Report 126}, year = 2001 }
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  A 3D laser range finder for autonomous mobile robots. Surmann, H.; Lingemann, K.; Nüchter, A.; Hertzberg, J. In Proceedings of the 32nd International Symposium on Robotics (ISR ’01), pp. 153–158. Seoul, Korea, 2001.
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  This paper presents a high quality, low cost 3D laser range finder designed for autonomous mobile systems. The 3D laser is built on the bas e of a 2D range finder by the extension with a standard servo. The servo is controlled by a computer running RT-Linux. The scan resolution (5 cm) f or a complete 3D scan of an area of 150 (h) 90 (v) degree is up to 115000 points and can be grabbed in 12 seconds. Standard resolutions e.g. 150 (h) 90 (v) degree with 22500 points are grabbed in 4 seconds. While scanning, different online algorithms for line and surface detection are applied to the data. Object segmentation and detection are done offline after the scan. The implemented software modules detect overhanging objects blocking t he path of the robot. With the proposed approach a cheap, precise, reliable and real-time capable 3D sensor for autonomous mobile robots is availabl e and the robot navigation and recognition in real-time is improved. 1. Introduction Prognoses at the beginning of the nineties claimed for the new millennium a number of about 50.000 independently operating autonomous service robots in different areas of production and service sectors [1]. The reality is different. In industrial environments guided vehicles, i.e. vehicles guided by a magnetic or optical track are standard [2]. Autonomous mobile service systems, i.e. systems not restricted by a track, are used extremely rarely although many research groups are working on this since sev eral years particularly with mobile systems for transportation tasks, e.g. [3, 4, 5, 6]. One of several reasons for the gap between prognoses and r eality is the lack of good, cheap and fast sensors that allow the robots to sense the environment in real-time and to act on the basis of the acquir ed data. This paper presents a 3D laser range finder designed for autonomous mobile systems (fig. 1). A large number of today's autonomous robots us e 2D laser range finders as a proximity sensor. They are very fast (processing time 30 ms), precise ( 1 cm, ) and becoming cheaper (\$3000) since th ere are at least two competing products [7, 8].

  @inproceedings{ISR2001, abstract = {This paper presents a high quality, low cost 3D laser range finder designed for autonomous mobile systems. The 3D laser is built on the bas e of a 2D range finder by the extension with a standard servo. The servo is controlled by a computer running RT-Linux. The scan resolution (5 cm) f or a complete 3D scan of an area of 150 (h) 90 (v) degree is up to 115000 points and can be grabbed in 12 seconds. Standard resolutions e.g. 150 (h) 90 (v) degree with 22500 points are grabbed in 4 seconds. While scanning, different online algorithms for line and surface detection are applied to the data. Object segmentation and detection are done offline after the scan. The implemented software modules detect overhanging objects blocking t he path of the robot. With the proposed approach a cheap, precise, reliable and real-time capable 3D sensor for autonomous mobile robots is availabl e and the robot navigation and recognition in real-time is improved. 1. Introduction Prognoses at the beginning of the nineties claimed for the new millennium a number of about 50.000 independently operating autonomous service robots in different areas of production and service sectors [1]. The reality is different. In industrial environments guided vehicles, i.e. vehicles guided by a magnetic or optical track are standard [2]. Autonomous mobile service systems, i.e. systems not restricted by a track, are used extremely rarely although many research groups are working on this since sev eral years particularly with mobile systems for transportation tasks, e.g. [3, 4, 5, 6]. One of several reasons for the gap between prognoses and r eality is the lack of good, cheap and fast sensors that allow the robots to sense the environment in real-time and to act on the basis of the acquir ed data. This paper presents a 3D laser range finder designed for autonomous mobile systems (fig. 1). A large number of today's autonomous robots us e 2D laser range finders as a proximity sensor. They are very fast (processing time 30 ms), precise ( 1 cm, ) and becoming cheaper (\$3000) since th ere are at least two competing products [7, 8].}, address = {Seoul, Korea}, author = {Surmann, H. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J.}, booktitle = {Proceedings of the 32nd International Symposium on Robotics (ISR '01)}, keywords = {imported}, month = {04}, pages = {153–158}, title = {A 3{D} laser range finder for autonomous mobile robots}, year = 2001 }
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  Fast acquiring and analysis of three dimensional laser range data. Surmann, H.; Lingemann, K.; Nüchter, A.; Hertzberg, J. In Proceedings of the 6th International Fall Workshop Vision, Modeling, and Visualization (VMV ’01), pp. 59–66. Stuttgart, Germany, 2001.
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  @inproceedings{VMV2001, address = {Stuttgart, Germany}, author = {Surmann, H. and Lingemann, K. and N{\"u}chter, A. and Hertzberg, J.}, booktitle = {Proceedings of the 6th International Fall Workshop Vision, Modeling, and Visualization (VMV '01)}, keywords = {myown}, month = 11, pages = {59–66}, title = {{F}ast acquiring and analysis of three dimensional laser range data}, year = 2001 }
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  Ein 3D-Laserscanner für autonome mobile Roboter. Nüchter, A.; Lingemann, K. In Tagungsband zum 3. Fachwissenschaftlichen Informatikkongress - Informatiktage 2001, pp. 89–92. Bad Schussenried, Germany, 2001.
  • [ BibTeX ]
  @inproceedings{IT2001, address = {Bad Schussenried, Germany}, author = {N{\"u}chter, A. and Lingemann, K.}, booktitle = {Tagungsband zum 3. Fachwissenschaftlichen Informatikkongress - Informatiktage 2001}, keywords = {imported}, month = 11, pages = {89–92}, title = {Ein 3{D}-{L}aserscanner f{\"u}r autonome mobile {R}oboter}, year = 2001 }