Offline Time-Independent Multi-Agent Path Planning
This addresses path planning for agents in asynchronous settings, but it appears incremental as it builds on existing multi-agent planning concepts with a specific timing-independent twist.
The paper tackles the problem of planning paths for multiple agents in asynchronous distributed environments where agents cannot share resources and have no timing knowledge, by introducing OTIMAPP and presenting solution conditions, complexity, solvers, and robotic applications.
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.