Fault-Tolerant Offline Multi-Agent Path Planning
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 10 of its 25 references that are in the map. First posted on arXiv 25 Nov 2022.
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10 of 25 references.
References · 10
- 2019Multi-Agent Pathfinding: Definitions, Variants, and Benchmarkscited by 199
- 2018PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learningcited by 90
- 2014Prioritized Planning Algorithms for Trajectory Coordination of Multiple Mobile Robotscited by 19
- 2021Iterative Refinement for Real-Time Multi-Robot Path Planningcited by 12
- 2021Beyond Robustness: A Taxonomy of Approaches towards Resilient Multi-Robot Systemscited by 12
- 2018Resilient Active Target Tracking with Multiple Robotscited by 10
- 2020Robust Multiple-Path Orienteering Problem: Securing Against Adversarial Attackscited by 8
- 2021Offline Time-Independent Multi-Agent Path Planningcited by 5
- 2020Robust Multi-Agent Task Assignment in Failure-Prone and Adversarial Environmentscited by 1
- 2021Active Modular Environment for Robot Navigationcited by 1
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