Improved Performance of Asymptotically Optimal Rapidly Exploring Random Trees

Boardman, Beth; Harden, Troy; Martínez, Sonia

doi:10.1115/1.4040970

Improved Performance of Asymptotically Optimal Rapidly Exploring Random Trees

Journal Article · Mon Aug 20 00:00:00 EDT 2018 · Journal of Dynamic Systems, Measurement, and Control

DOI:https://doi.org/10.1115/1.4040970· OSTI ID:1467259

^[1]; ^[1]; Martínez, Sonia ^[2]

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

Three algorithms that improve the performance of the asymptotically optimal Rapidly exploring Random Tree (RRT*) are presented here. First, we introduce the Goal Tree (GT) algorithm for motion planning in dynamic environments where unexpected obstacles appear sporadically. The GT reuses the previous RRT* by pruning the affected area and then extending the tree by drawing samples from a shadow set. The shadow is the subset of the free configuration space containing all configurations that have geodesics ending at the goal and are in conflict with the new obstacle. Smaller, well defined, sampling regions are considered for Euclidean metric spaces and Dubins' vehicles. Next, the Focused-Refinement (FR) algorithm, which samples with some probability around the first path found by an RRT*, is defined. The third improvement is the Grandparent-Connection (GP) algorithm, which attempts to connect an added vertex directly to its grandparent vertex instead of parent. The GT and GP algorithms are both proven to be asymptotically optimal. Finally, the three algorithms are simulated and compared for a Euclidean metric robot, a Dubins' vehicle, and a seven degrees-of-freedom manipulator.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC52-06NA25396

OSTI ID:: 1467259

Report Number(s):: LA-UR-17-24020

Journal Information:: Journal of Dynamic Systems, Measurement, and Control, Journal Name: Journal of Dynamic Systems, Measurement, and Control Journal Issue: 1 Vol. 141; ISSN 0022-0434

Publisher:: ASMECopyright Statement

Country of Publication:: United States

Language:: English

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