Virtual Obstacles Regulation for Multi-Agent Path Finding

Multi-agent path finding (MAPF) involves finding collision-free paths for multiple agents while minimizing the total path costs. Explicit estimation conflict-based search (EECBS) represents a state-of-the-art variant of the widely used conflict-based search (CBS) method, offering bounded-suboptimal solutions. However, both CBS and its variants rely on pairwise conflict resolution methods. A conflict boom means many conflicts occur at one location, which frequently exists in scenarios that a large number of agents operate in small space, and usually leads to heavy computational burden. The location that conflict boom occurs is regarded as conflict boom vertex. This letter proposes a novel method, the Virtual Obstacles Regulation, to expedite algorithmic solving processes (such as EECBS) for MAPF. The proposed method identifies conflicts boom vertices and strategically regulates them as global or local virtual obstacles to circumvent concentrated conflicts. Then, the pairwise conflict resolution processes on conflicts boom vertices are significantly simplified, hence accelerating overall algorithm runtime–often dominated by conflict resolution. Numerical studies validate the efficacy of this approach.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-11-08
DOI
https://doi.org/10.1109/lra.2024.3494653
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25

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article

Virtual Obstacles Regulation for Multi-Agent Path Finding

S. H. Zeng, Li Chai
1 citations
IEEE Robotics and Automation Letters
Robotic Path Planning Algorithms
0.25
article

Virtual Obstacles Regulation for Multi-Agent Path Finding

S. H. Zeng, Li Chai
article en
1 citations

Abstract

Multi-agent path finding (MAPF) involves finding collision-free paths for multiple agents while minimizing the total path costs. Explicit estimation conflict-based search (EECBS) represents a state-of-the-art variant of the widely used conflict-based search (CBS) method, offering bounded-suboptimal solutions. However, both CBS and its variants rely on pairwise conflict resolution methods. A conflict boom means many conflicts occur at one location, which frequently exists in scenarios that a large number of agents operate in small space, and usually leads to heavy computational burden. The location that conflict boom occurs is regarded as conflict boom vertex. This letter proposes a novel method, the Virtual Obstacles Regulation, to expedite algorithmic solving processes (such as EECBS) for MAPF. The proposed method identifies conflicts boom vertices and strategically regulates them as global or local virtual obstacles to circumvent concentrated conflicts. Then, the pairwise conflict resolution processes on conflicts boom vertices are significantly simplified, hence accelerating overall algorithm runtime–often dominated by conflict resolution. Numerical studies validate the efficacy of this approach.

IEEE Robotics and Automation LettersVol. 9(12)
State Key Laboratory of Industrial Control Technology (CN), Wuhan University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 45%
Robotic Path Planning Algorithms
0.25
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