IJCAI 2022poster9 citations

Offline Time-Independent Multi-Agent Path Planning

Keisuke Okumura, François Bonnet, Yasumasa Tamura, Xavier Défago

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.

Planning and Scheduling: DistributedMulti-agent PlanningAgent-based and Multi-agent Systems: Multi-agent PlanningPlanning and Scheduling: Planning under UncertaintyPlanning and Scheduling: Robot PlanningRobotics: Motion and Path Planning
BibTeX
@inproceedings{ijcai2022p645,
  title     = {Offline Time-Independent Multi-Agent Path Planning},
  author    = {Okumura, Keisuke and Bonnet, François and Tamura, Yasumasa and Défago, Xavier},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Lud De Raedt},
  pages     = {4649--4656},
  year      = {2022},
  month     = {7},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2022/645},
  url       = {https://doi.org/10.24963/ijcai.2022/645},
}
Offline Time-Independent Multi-Agent Path Planning · IJCAI 2022