Distributionally Safe Path Planning: Wasserstein Safe RRT

Lathrop, Paul; Boardman, Beth; Martinez, Sonia

doi:10.1109/lra.2021.3128696

Distributionally Safe Path Planning: Wasserstein Safe RRT

Journal Article · Wed Nov 17 00:00:00 EST 2021 · IEEE Robotics and Automation Letters

DOI:https://doi.org/10.1109/lra.2021.3128696· OSTI ID:1878051

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Univ. of California, San Diego, CA (United States); Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Univ. of California, San Diego, CA (United States)

In this paper, we propose a Wasserstein metric-based random path planning algorithm. Wasserstein Safe RRT (W-Safe RRT) provides finite-sample probabilistic guarantees on the safety of a returned path in an uncertain obstacle environment. Vehicle and obstacle states are modeled as distributions based upon state and model observations. Additionally, we define limits on distributional sampling error so the Wasserstein distance between a vehicle state distribution and obstacle distributions can be bounded. This enables the algorithm to return safe paths with a confidence bound through combining finite sampling error bounds with calculations of the Wasserstein distance between discrete distributions. W-Safe RRT is compared against a baseline minimum encompassing ball algorithm, which ensures balls that minimally encompass discrete state and obstacle distributions do not overlap. The improved performance is verified in a 3D environment using single, multi, and rotating non-convex obstacle cases, with and without forced obstacle error in adversarial directions, showing that W-Safe RRT can handle poorly modeled complex environments.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: US Office of Naval Research (ONR); USDOE

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1878051

Report Number(s):: LA-UR-21-25559

Journal Information:: IEEE Robotics and Automation Letters, Journal Name: IEEE Robotics and Automation Letters Journal Issue: 1 Vol. 7; ISSN 2377-3766

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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Distributionally Safe Path Planning: Wasserstein Safe RRT

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