Probabilistically Safe Corridors to Guide Sampling-Based Motion Planning

1 Jan 2019Jinwook HuhOmur ArslanDaniel D. Lee

In this paper, we introduce a new probabilistically safe local steering primitive for sampling-based motion planning in complex high-dimensional configuration spaces. Our local steering procedure is based on a new notion of a convex probabilistically safe corridor that is constructed around a configuration using tangent hyperplanes of confidence ellipsoids of Gaussian mixture models learned from prior collision history... (read more)

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