AAAI Publications, Twenty-Fourth International Conference on Automated Planning and Scheduling

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C-FOREST: Parallel Shortest-Path Planning with Super Linear Speedup
Michael Otte, Nikolaus Correll

Last modified: 2014-05-11


In (Otte and Correll 2013) we present C-FOREST, a parallelization framework for single-query sampling-based shortest-path planning algorithms. C-FOREST has been observed to have super linear speedup on many problems, e.g., paths of quality Ltarget are found 350X faster by 64 CPUs working in parallel than by 1 CPU. In (Otte and Correll 2013) C-FOREST is tested in conjunction with the RRT* algorithm. In the current work we perform additional experiments that show C-FOREST provides similar advantages when used conjunction with the SPRT algorithm. This reinforces our original claim that C-FOREST is generally applicable to a wide range of sampling based motion planning algorithms.


Super-Linear Speedup; Algorithms; Path Planning; Motion Planning; Multi-Agent; Sampling Based Motion Planning; Robotics; Parallel Computing; Distributed Computing

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