Offline Time-Independent Multi-Agent Path Planning

Keisuke Okumura, François Bonnet, Yasumasa Tamura, Xavier Défago

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Main Track. Pages 4649-4656.

https://doi.org/10.24963/ijcai.2022/645

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Abstract

This paper studies a novel planning problem for multiple agents that cannot share holding resources, named OTIMAPP (Offline Time-Independent Multi-Agent Path Planning). Given a graph and a set of start-goal pairs, the problem consists in assigning a path to each agent such that every agent eventually reaches their goal without blocking each other, regardless of how the agents are being scheduled at runtime. The motivation stems from the nature of distributed environments that agents take actions fully asynchronous and have no knowledge about those exact timings of other actors. We present solution conditions, computational complexity, solvers, and robotic applications.

Keywords

  • Planning and Scheduling: Distributed; Multi-agent Planning
  • Agent-based and Multi-agent Systems: Multi-agent Planning
  • Planning and Scheduling: Planning under Uncertainty
  • Planning and Scheduling: Robot Planning
  • Robotics: Motion and Path Planning
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