Asymptotically Optimal Sampling-Based Motion Planning Methods

Gammell, Jonathan D.; Strub, Marlin P.

doi:10.48550/arxiv.2009.10484

Cited by 1 publication

(1 citation statement)

References 47 publications

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“…Motion planning [51] is a well studied topic which has been successfully applied to a wide range of problem domains [62]. One of the most promising paradigms to solve motion planning problems are (optimal) sampling-based planner [45,82,81,6,25]. However, those planner might become inefficient in state spaces which are too high-dimensional [67], contain intricate constraints [42] or narrow passages [53].…”

Section: A Generating Admissible Heuristicsmentioning

confidence: 99%

Section Patterns: Efficiently Solving Narrow Passage Problems in Multilevel Motion Planning

Orthey¹,

Toussaint²

2020

Preprint

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Sampling-based planning methods often become inefficient due to narrow passages. Narrow passages induce a higher runtime, because the chance to sample them becomes vanishingly small. In recent work, we showed that narrow passages can be approached by relaxing the problem using admissible lowerdimensional projections of the state space. Those relaxations often increase the volume of narrow passages under projection. Solving the relaxed problem is often efficient and produces an admissible heuristic we can exploit. However, given a base path, i.e. a solution to a relaxed problem, there are currently no tailored methods to efficiently exploit the base path. To efficiently exploit the base path and thereby its admissible heuristic, we develop section patterns, which are solution strategies to efficiently exploit base paths in particular around narrow passages. To coordinate section patterns, we develop the pattern dance algorithm, which efficiently coordinates section patterns to reactively traverse narrow passages. We combine the pattern dance algorithm with previously developed multilevel planning algorithms and benchmark them on challenging planning problems like the Bugtrap, the double L-shape, an egress problem and on four pregrasp scenarios for a 37 degrees of freedom shadow hand mounted on a KUKA LWR robot. Our results confirm that section patterns are useful to efficiently solve high-dimensional narrow passage motion planning problems.

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