Abstract | ||
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This paper studies a novel planning problem for multiple agents moving on graphs that we call offline time-independent multi-agent path planning (OTIMAPP). The motivation is to overcome time uncertainties in multi-agent scenarios where we cannot expect agents to act perfectly following timed plans, e.g., executions with mobile robots. For this purpose, OTIMAPP abandons all timing assumptions; it is offline planning that assumes event-driven executions without or less run-time effort. The problem is finding plans to be terminated correctly in any action orders of agents, i.e., guaranteeing that all agents eventually reach their destinations. We address a bunch of questions for this problem: required conditions for feasible solutions, computational complexity, comparison with well-known other multi-agent problems, construction of solvers, effective relaxation of a solution concept, and how to implement the plans by actual robots. Throughout the paper, we establish the foundation of OTIMAPP and demonstrate its utility. A video is available at https://kei18.github.io/otimapp. |
Year | DOI | Venue |
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2022 | 10.24963/ijcai.2022/645 | European Conference on Artificial Intelligence |
Keywords | DocType | Citations |
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 | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
---|---|---|---|
Keisuke Okumura | 1 | 1 | 2.73 |
François Bonnet | 2 | 0 | 0.68 |
Yasumasa Tamura | 3 | 0 | 0.68 |
xavier defago | 4 | 188 | 22.39 |