Optimizing Schedules for Prioritized Path Planning of Multi-Robot Systems

The coordination of the motions of the robots is one of the fundamental problems for multi-robot systems. A popular approach to avoid planning in the high-dimensional composite configuration space are prioritized and decoupled techniques. While these methods are very efficient, they have two major drawbacks. First, they are incomplete, i.e. they sometimes fail to find a solution even if one exists, and second, the resulting solutions are often not optimal. They furthermore leave open how to assign the priorities to the individual robots. In this paper we present a method for optimizing priority schemes for such prioritized and decoupled planning techniques. Our approach performs a randomized search with hill-climbing to find solutions and to minimize the overall path lengths. The technique has been implemented and tested on real robots and in extensive simulation runs. The experimental results demonstrate that our method is able to seriously reduce the number of failures and to significantly reduce the overall path length for different prioritized and decoupled path planning techniques and even for large teams of robots.