A batch informed sampling-based algorithm for fast anytime asymptotically-optimal motion planning in cluttered environments

•Present an anytime asymptotically-optimal motion planning algorithm.•A strategy is proposed that balances the “lazy” and “non-lazy” optimal search.•Analyze the swift convergence and computational complexity for the algorithm.•The proposed algorithm is comprehensively evaluated by rigorous experimen...

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Bibliographic Details
Published in:	Expert systems with applications Vol. 144; p. 113124
Main Authors:	Xu, Jing, Song, Kechen, Dong, Hongwen, Yan, Yunhui
Format:	Journal Article
Language:	English
Published:	New York Elsevier Ltd 15.04.2020 Elsevier BV
Subjects:	Algorithms Anytime algorithm Asymptotic optimality Asymptotic properties Cost analysis Expert systems Graph theory Modules Motion planning Motion stability Optimal path planning Robustness (mathematics) Sampling Searching Motion planning Asymptotic optimality Optimal path planning Anytime algorithm
ISSN:	0957-4174, 1873-6793
Online Access:	Get full text
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