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 |
| Zugehörige Links: | |
| 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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