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.
@INPROCEEDINGS{Roy02a,
AUTHOR = {Roy, N. and Thrun, S.},
TITLE = {Motion Planning Through Policy Search},
YEAR = {2002},
BOOKTITLE = {Proceedings of the Conference on Intelligent Robots
and Systems (IROS)},
ADDRESS = {Lausanne, Switzerland}
}