3D Modeling, Distance and Gradient Computation for Motion Planning: A Direct GPGPU Approach
DLR Institute of Robotics and Mechatronics, 82234 Wessling, Germany
IEEE International Conference on Robotics and Automation (ICRA’13), 2013
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.
March 12, 2013 by hgpu