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Accurate Pose Prediction on Signed Distance Fields for Mobile Ground Robots in Rough Terrain

Oehler, Martin ; Stryk, Oskar von (2023)
Accurate Pose Prediction on Signed Distance Fields for Mobile Ground Robots in Rough Terrain.
2023 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR'23). Fukushima, Japan (13.11. - 15.11.2023)
doi: 10.1109/SSRR59696.2023.10499944
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Autonomous locomotion for mobile ground robots in unstructured environments such as waypoint navigation or flipper control requires a sufficiently accurate prediction of the robot-terrain interaction. Heuristics like occupancy grids or traversability maps are widely used but limit actions available to robots with active flippers as joint positions are not taken into account. We present a novel iterative geometric method to predict the 3D pose of mobile ground robots with active flippers on uneven ground with high accuracy and online planning capabilities. This is achieved by utilizing the ability of signed distance fields to represent surfaces with sub-voxel accuracy. The effectiveness of the presented approach is demonstrated on two different tracked robots in simulation and on a real platform. Compared to a tracking system as ground truth, our method predicts the robot position and orientation with an average accuracy of 3.11 cm and 3.91°, outperforming a recent heightmap-based approach. The implementation is made available as an open-source ROS package.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2023
Autor(en): Oehler, Martin ; Stryk, Oskar von
Art des Eintrags: Bibliographie
Titel: Accurate Pose Prediction on Signed Distance Fields for Mobile Ground Robots in Rough Terrain
Sprache: Englisch
Publikationsjahr: November 2023
Verlag: IEEE
Buchtitel: Proceedings of the 2023 IEEE International Symposium on Safety, Security, and Rescue Robotics
Veranstaltungstitel: 2023 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR'23)
Veranstaltungsort: Fukushima, Japan
Veranstaltungsdatum: 13.11. - 15.11.2023
DOI: 10.1109/SSRR59696.2023.10499944
URL / URN: https://ieeexplore.ieee.org/document/10499944
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Kurzbeschreibung (Abstract):

Autonomous locomotion for mobile ground robots in unstructured environments such as waypoint navigation or flipper control requires a sufficiently accurate prediction of the robot-terrain interaction. Heuristics like occupancy grids or traversability maps are widely used but limit actions available to robots with active flippers as joint positions are not taken into account. We present a novel iterative geometric method to predict the 3D pose of mobile ground robots with active flippers on uneven ground with high accuracy and online planning capabilities. This is achieved by utilizing the ability of signed distance fields to represent surfaces with sub-voxel accuracy. The effectiveness of the presented approach is demonstrated on two different tracked robots in simulation and on a real platform. Compared to a tracking system as ground truth, our method predicts the robot position and orientation with an average accuracy of 3.11 cm and 3.91°, outperforming a recent heightmap-based approach. The implementation is made available as an open-source ROS package.

Freie Schlagworte: emergenCITY, emergenCITY_CPS
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Simulation, Systemoptimierung und Robotik
LOEWE
LOEWE > LOEWE-Zentren
LOEWE > LOEWE-Zentren > emergenCITY
Hinterlegungsdatum: 08 Mai 2024 06:14
Letzte Änderung: 08 Mai 2024 06:14
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