Fast online collision avoidance for mobile service robots through potential fields on 3D environment data processed on GPUs

Publikationstyp
Konferenz
Autor(en)
Juelg, Christian and Hermann, Andreas and Roennau, Arne and Dillmann, Ruediger
Jahr
2017
Notiz
unpublished, approved for publication
Buchtitel
2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)
Hochschule
Karlsruher Institut für Technologie
Abstract
This paper demonstrates the fitness of massively parallel exact Euclidean distance transform (EDT) computation for fast 3D online motion planning with potential field and wavefront planners. We combine point-cloud sensor data to gather detailed 3D voxel maps of complex environments. Unlike other approaches, we do not use 3D polygon meshes or reduce the environment to 2D or 2.5D models to improve planning times. The evaluation shows that fast sub-second local and global planning times on the basis of GPU EDT are possible.
Link
https://www.researchgate.net/publication/324024262_Fast_online_collision_avoidance_for_mobile_service_robots_through_potential_fields_on_3D_environment_data_processed_on_GPUs
DOI
10.1109/ROBIO.2017.8324535
Forschungsfelder
Service-Robotik und mobile Manipulation
Projekt
HORSE – Smarte Robotik-Lösungen ermöglichen KMUs den Einsatz neuester Robotertechnologien in dynamischen Montage Prozessen
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Eingetragen von
Christian Juelg