FBi-RRT: a path planning algorithm for manipulators with heuristic node expansion

This paper is concerned with the problem of collision-free path planning for manipulators in multi-obstacle scenarios. Aiming at overcoming the deficiencies of existing algorithms in excessive time consumption and poor expansion quality, a path planning algorithm named Fast Bi-directional Rapidly-ex...

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Veröffentlicht in:Robotica Jg. 42; H. 3; S. 644 - 659
Hauptverfasser: Xiao, Guangzhou, Zhang, Lixian, Wu, Tong, Han, Yuejiang, Ding, Yihang, Han, Chengzhe
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cambridge, UK Cambridge University Press 01.03.2024
Schlagworte:
Algorithms
Barriers
Collision avoidance
Expansion
Heuristic
Nodes
Path planning
Strategy
robotic manipulator
sampling-based algorithm
rapidly exploring random tree
path planning
time consumption
ISSN:0263-5747, 1469-8668
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Zusammenfassung:This paper is concerned with the problem of collision-free path planning for manipulators in multi-obstacle scenarios. Aiming at overcoming the deficiencies of existing algorithms in excessive time consumption and poor expansion quality, a path planning algorithm named Fast Bi-directional Rapidly-exploring Random Tree (FBi-RRT) with novel heuristic node expansion is proposed, which includes a selective-expansion strategy and a vertical-exploration strategy. The selective-expansion strategy is designed to guide the selection of the nearest-neighbor node to avoid the repeated expansion failure, thereby shortening the overall planning time. Also, the vertical-exploration strategy is developed to regulate the expansion direction of the collision nodes to escape from the obstacle space with less blindness, thus improving the expansion quality and further reducing time cost. Compared with previous planning algorithms, FBi-RRT can generate a feasible path for manipulators in a drastically shorter time. To validate the effectiveness of the proposed heuristic node expansion, FBi-RRT is conducted on a 6-DOF manipulator and tested in five scenarios. The experimental results demonstrate that FBi-RRT outperforms the existing methods in time consumption and expansion quality.
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ISSN:0263-5747
1469-8668
DOI:10.1017/S0263574723001674