PLRC* - A piecewise linear regression complex for approximating optimal robot motion.

IROS(2020)

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摘要
Discrete graphs are commonly used to approximately represent configuration spaces used in robot motion planning. This paper explores a representation in which the costs of crossing local regions of the configuration space are represented using piecewise linear regression (PLR). We explore a few simple motion planning problems, and show that for these problems, the memory required to store the representation compares favorably to that required for standard discrete vertex-and-edge models, while preserving the quality of paths returned from searches.
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关键词
PLRC,piecewise linear regression complex,optimal robot motion,discrete graphs,configuration space,robot motion planning,local regions,discrete vertex-and-edge models
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