Motion Planning through Policy Search
Nicholas Roy and Sebastian Thrun
We propose a motion planning algorithm for performing policy search in the full pose and velocity space of a mobile robot. By comparison, existing techniques optimize high-level plans, but fail to optimize the low-level motion controls. We use policy search in a high dimensional control space to find plans that lead to measurably better motion planning. Our experimental results suggest that our approach leads to superior robot motion than many existing techniques.
The full paper is available in gzipped Postscript and PDF