Offline Time-Independent Multi-Agent Path Planning
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 May 2021.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 0; 2025: 2.
5 papers.
- 2023Learning Team-Based Navigation: A Review of Deep Reinforcement Learning Techniques for Multi-Agent Pathfindingcited by 6
- 2023Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Executioncited by 6
- 2025Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfindingcited by 3
- 2022Fault-Tolerant Offline Multi-Agent Path Planningcited by 0
- 2025Multi-Agent Pathfinding Under Team-Connected Communication Constraint via Adaptive Path Expansion and Dynamic Leadingcited by 0
- 2025Where Paths Collide: A Comprehensive Survey of Classic and Learning-Based Multi-Agent Pathfinding25 May 2025
- 2025Multi-Agent Pathfinding Under Team-Connected Communication Constraint via Adaptive Path Expansion and Dynamic Leading6 Jan 2025
- 2023Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution30 Dec 2023
- 2023Learning Team-Based Navigation: A Review of Deep Reinforcement Learning Techniques for Multi-Agent Pathfinding11 Aug 2023
- 2022Fault-Tolerant Offline Multi-Agent Path Planning25 Nov 2022