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Conference Papers Year : 2023

Fault-Tolerant Offline Multi-Agent Path Planning


We study a novel graph path planning problem for multiple agents that may crash at runtime, and block part of the workspace. In our setting, agents can detect neighboring crashed agents, and change followed paths at runtime. The objective is then to prepare a set of paths and switching rules for each agent, ensuring that all correct agents reach their destinations without collisions or deadlocks, despite unforeseen crashes of other agents. Such planning is attractive to build reliable multi-robot systems. We present problem formalization, theoretical analysis such as computational complexities, and how to solve this offline planning problem.

Dates and versions

ird-04197988 , version 1 (06-09-2023)



Keisuke Okumura, Sébastien Tixeuil. Fault-Tolerant Offline Multi-Agent Path Planning. 37th AAAI Conference on Artificial Intelligence, Feb 2023, Washington DC, United States. pp.11647-11654, ⟨10.1609/aaai.v37i10.26376⟩. ⟨ird-04197988⟩
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