| Art der Veröffentlichung: |
Artikel in Konferenzband |
| Autor: |
René Wagner, Udo Frese, Berthold Bäuml |
| Titel: |
3D Modeling, Distance and Gradient Computation for Motion Planning: A Direct GPGPU Approach |
| Buch / Sammlungs-Titel: |
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany |
| Erscheinungsjahr: |
2013 |
| Abstract / Kurzbeschreibung: |
The Kinect sensor and KinectFusion algorithm have revolutionized environment modeling. We bring these advances to optimization-based motion planning by computing the obstacle and self-collision avoidance objective functions and their gradients directly from the KinectFusion model on the GPU without ever transferring any model to the CPU. Based on this, we implement a proof-of-concept motion planner which we validate in an experiment with a 19-DOF humanoid robot using real data from a tabletop work space. The summed-up time from taking the first look at the scene until the planned path avoiding an obstacle on the table is executed is only three seconds. |
| PDF Version: |
http://www.informatik.uni-bremen.de/agebv/downloads/published/wagner_icra_13.pdf |
| Schlagworte: |
kinect motionplanning optimization humanoid robot justin gpgpu gpu cuda |
| Status: |
Reviewed |
| Letzte Aktualisierung: |
24. 08. 2016 |
