Path planning in 1000+ dimensions using a task-space Voronoi bias

• Published in: 2009 IEEE International Conference on Robotics and Automation pp. 2061 - 2067
• Main Authors: Shkolnik, A., Tedrake, R.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2009
• Subjects: Adaptive control; Kinematics; Manipulator dynamics; Motion planning; Orbital robotics; Path planning; Process design; Process planning; State feedback; Trajectory
• ISBN: 1424427886; 9781424427888
• ISSN: 1050-4729; 2577-087X
• DOI: 10.1109/ROBOT.2009.5152638

The reduction of the kinematics and/or dynamics of a high-DOF robotic manipulator to a low-dimension ldquotask spacerdquo has proven to be an invaluable tool for designing feedback controllers. When obstacles or other kinodynamic constraints complicate the feedback design process, motion planning techniques can often still find feasible paths, but these techniques are typically implemented in the high-dimensional configuration (or state) space. Here we argue that providing a Voronoi bias in the task space can dramatically improve the performance of randomized motion planners, while still avoiding non-trivial constraints in the configuration (or state) space. We demonstrate the potential of task-space search by planning collision-free trajectories for a 1500 link arm through obstacles to reach a desired end-effector position.