A two-level search algorithm for motion planning

Abstract

A two-level search algorithm for motion planning is presented in this paper. The algorithm combines a multiheuristic local search algorithm with a subgoal graph based global guidance. A novel feature of the planner is that it can adjust the balance between local and global planning. As the experimental data suggests that the optimal balance depends on the problem, a scheduling mechanism is added to the algorithm to adjust the balance during planning. The resulting motion planner is capable of solving very difficult motion planning problems.