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Offline Time-Independent Multiagent Path Planning
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AI
DOI：10.1109/TRO.2023.3258690.png)
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摘要
En 中文
This study examines a novel planning problem for multiple agents that cannot share holding resources, named Offline Time-Independent Multiagent Path Planning (OTIMAPP). Given a graph and a set of start-goal pairs, the problem to be addressed is assigning a path to each agent, such that every agent eventually reaches its destination without blocking others, regardless of when each agent starts and finishes each own action. This motivation stems from timing uncertainties, including the reality gaps between planning and robot execution. In contrast to conventional solution, concepts of multirobot path planning that rely on timings, once OTIMAPP solutions are obtained, they can be executed without any synchronization between robot actions. Moreover, there is a theoretical guarantee that all robots eventually reach their destinations, provided they avoid interrobot collisions. This study attempts to establish OTIMAPP both theoretically and practically. Specifically, we present a formalization of the problem, solution conditions based on a categorization of deadlocks, computational complexities showing that OTIMAPP is computationally intractable, practical relaxation of the solution concept, two algorithms to solve OTIMAPP based on multiagent pathfinding algorithms, empirical results showing large OTIMAPP instances can be solved to some extent, as well as robot demonstrations of asynchronous OTIMAPP execution.
Keyword:
System recovery
Robots
Robot kinematics
Collision avoidance
Timing
Schedules
Uncertainty
Asynchronous execution
deadlock prevention
Index Terms
multirobot coordination
timing uncertainties
path planning
期刊
IF:
10.5
论文数:
3.3K
被引数:
2.8W
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