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AAAI 2023

Fault-Tolerant Offline Multi-Agent Path Planning

Conference Paper AAAI Technical Track on Multiagent Systems Artificial Intelligence

Abstract

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.

Authors

Keywords

  • MAS: Coordination and Collaboration
  • MAS: Multiagent Planning
  • PRS: Plan Execution and Monitoring
  • ROB: Motion and Path Planning
  • ROB: Multi-Robot Systems
  • SO: Heuristic Search

Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
900809681370075573