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RH-ECBS: enhanced conflict-based search for MRPP with region heuristics

Part of: The 40th Anniversary of Robotica

Published online by Cambridge University Press:  27 August 2024

Zhangchao Pan Open the ORCID record for Zhangchao Pan [Opens in a new window] ,
Runhua Wang ,
Qingchen Bi ,
Xuebo Zhang  and
Jingjin Yu Open the ORCID record for Jingjin Yu [Opens in a new window]
Zhangchao Pan
Affiliation:
College of Artificial Intelligence, Nankai University, Tianjin, China
Runhua Wang*
Affiliation:
College of Artificial Intelligence, Nankai University, Tianjin, China
Qingchen Bi
Affiliation:
College of Artificial Intelligence, Nankai University, Tianjin, China
Xuebo Zhang
Affiliation:
College of Artificial Intelligence, Nankai University, Tianjin, China
Jingjin Yu
Affiliation:
Rutgers University New Brunswick, Computer Science New Brunswick, New Brunswick, USA
*
Corresponding author: Runhua Wang; Email: wrunhua@nankai.edu.cn
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Abstract

This paper proposes a novel two-layer framework based on conflict-based search and regional divisions to improve the efficiency of multi-robot path planning. The high-level layer targets the reduction of conflicts and deadlocks, while the low-level layer is responsible for actual path planning. Distinct from previous dual-level search frameworks, the novelties of this work are (1) subdivision of planning regions for each robot to decrease the number of conflicts encountered during planning; (2) consideration of the number of robots in the region during planning in the node expansion stage of A*, and (3) formal proof demonstrating the nonzero probability of the proposed method in obtaining a solution, along with providing the upper bound of the solution in a special case. Experimental comparisons with Enhanced Conflict-Based Search demonstrate that the proposed method not only reduces the number of conflicts but also achieves a computation time reduction of over 30%.

Keywords

mobile robotsmulti-robot systemmulti-robot path planningconflict-based search
Type
Research Article
Information
Robotica , First View , pp. 1 - 11
Copyright
© The Author(s), 2024. Published by Cambridge University Press

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