Workspace-Based Connectivity Oracle: An Adaptive Sampling Strategy for PRM Planning
نویسندگان
چکیده
This paper presents Workspace-based Connectivity Oracle (WCO), a new sampling strategy for probabilistic roadmap planning. WCO uses both domain knowledge—specifically, workspace geometry—and sampling history to construct a dynamic sampling distribution. WCO is composed of many component samplers, each based on a geometric feature of a robot. Each component sampler updates its distribution, using the workspace geometry and the current state of the roadmap being consructed. These component samplers are then combined through the adaptive hybrid sampling approach, based on their sampling histories. In the tests on rigid and articulated robots in 2-D and 3-D workspaces, WCO showed strong performance, compared with sampling strategies that use workspace information or dynamic sampling alone.
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