C-FOREST: Parallel Shortest-Path Planning with Super Linear Speedup

Authors

  • Michael Otte Massachusetts Institute of Technology
  • Nikolaus Correll University of Colorado at Boulder

DOI:

https://doi.org/10.1609/icaps.v24i1.13660

Keywords:

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

Abstract

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.

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Published

2014-05-11

How to Cite

Otte, M., & Correll, N. (2014). C-FOREST: Parallel Shortest-Path Planning with Super Linear Speedup. Proceedings of the International Conference on Automated Planning and Scheduling, 24(1), 532-535. https://doi.org/10.1609/icaps.v24i1.13660

Issue

Vol. 24 (2014): Twenty-Fourth International Conference on Automated Planning and Scheduling

Section

Journal Special Track