Multiple Query Probabilistic Roadmap Planning using Single Query Planning Primitives

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Abstract

We propose a combination of techniques that solve multiple queries for motion planning problems with single query planners. Our implementation uses a probabilistic roadmap method (PRM) with bidirectional rapidly exploring random trees (BI-RRT) as the local planner. With small modifications to the standard algorithms, we obtain a multiple query planner which is significantly faster and more reliable than its component parts. Our method provides a smooth spectrum between the PRM and BI-RRT techniques and obtains the advantages of both. We observed that the performance differences are most notable in planning instances with several rigid nonconvex robots in a scene with narrow passages. Our work is in the spirit of non-uniform sampling and refinement techniques used in earlier work on PRM.

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Bekris, K. E., Chen, B. Y., Ladd, A. M., Plaku, E., & Kavraki, L. E. (2003). Multiple Query Probabilistic Roadmap Planning using Single Query Planning Primitives. In IEEE International Conference on Intelligent Robots and Systems (Vol. 1, pp. 656–661). https://doi.org/10.1109/iros.2003.1250704

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