Optimizing schedules for prioritized path planning of multi-robot systems
The coordination of robot motions is one of the fundamental problems for multi-robot systems. A popular approach to avoid planning in the high-dimensional composite configuration space is the prioritized and decoupled technique. In this paper we present a method for optimizing priority schemes for such prioritized and decoupled planning technique. 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 greatly 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.