Cooperative Multi-Agent Path Finding: Beyond Path Planning and Collision Avoidance

• URL: http://arxiv.org/abs/2105.10993v1
• Date: Sun, 23 May 2021 18:25:46 GMT
• Title: Cooperative Multi-Agent Path Finding: Beyond Path Planning and Collision Avoidance
• Authors: Nir Greshler, Ofir Gordon, Oren Salzman, and Nahum Shimkin
• Abstract summary: We introduce the Cooperative Multi-Agent Path Finding (Co-MAPF) problem, an extension to the classical MAPF problem. In this setting, a group of autonomous agents operate in a shared environment and have to complete cooperative tasks. We introduce Cooperative Conflict-Based Search (Co-CBS), a CBS-based algorithm for solving the problem optimally for a wide set of Co-MAPF problems.
• Score: 5.785285760361722
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce the Cooperative Multi-Agent Path Finding (Co-MAPF) problem, an extension to the classical MAPF problem, where cooperative behavior is incorporated. In this setting, a group of autonomous agents operate in a shared environment and have to complete cooperative tasks while avoiding collisions with the other agents in the group. This extension naturally models many real-world applications, where groups of agents are required to collaborate in order to complete a given task. To this end, we formalize the Co-MAPF problem and introduce Cooperative Conflict-Based Search (Co-CBS), a CBS-based algorithm for solving the problem optimally for a wide set of Co-MAPF problems. Co-CBS uses a cooperation-planning module integrated into CBS such that cooperation planning is decoupled from path planning. Finally, we present empirical results on several MAPF benchmarks demonstrating our algorithm's properties.

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