[BibTeX] [RIS]
3D Modeling, Distance and Gradient Computation for Motion Planning: A Direct GPGPU Approach
Type of publication: Inproceedings
Citation: WagnerICRA13
Booktitle: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2013), Karlsruhe, Germany
Year: 2013
Abstract: 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.
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Keywords: kinect motionplanning optimization humanoid robot justin gpgpu gpu cuda
Authors Wagner, René
Frese, Udo
Bäuml, Berthold
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