Distributed Sampling-based Roadmap of Trees for large-scale motion planning

High-dimensional problems arising from complex robotic systems test the limits of current motion planners and require the development of efficient distributed motion planners that take full advantage of all the available resources. This paper shows how to effectively distribute the computation of the Sampling-based Roadmap of Trees (SRT) algorithm using a decentralized master-client scheme. The distributed SRT algorithm allows us to solve very high-dimensional problems that cannot be efficiently addressed with existing planners. Our experiments show nearly linear speedups with eighty processors and indicate that similar speedups can be obtained with several hundred processors.