Publication record · 18.cifr/1996.kavraki.prm-path-planning
18.cifr/1996.kavraki.prm-path-planningA new motion planning method, the probabilistic roadmap method (PRM), is presented. It constructs a probabilistic roadmap by randomly sampling the configuration space, retaining collision-free configurations, and connecting nearby configurations using a simple local planner. Queries are answered by connecting start and goal to the roadmap and searching for a path. The method is probabilistically complete and practical for high-dimensional C-spaces.
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PRM struggles in narrow C-space passages rarely hit by uniform sampling; non-uniform and bridge-test samplers were identified as needed follow-up. Dynamic environment extensions requiring incremental roadmap updates and tighter theoretical sample-complexity bounds remain open problems.