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Multi-Agent Path Finding (MAPF) is the problem of finding collision-freepaths for multiple agents from their start locations to end locations. Weconsider an extension to this problem, Precedence Constrained Multi-Agent PathFinding (PC-MAPF), wherein agents are assigned a sequence of planning tasksthat contain precedence constraints between them. PC-MAPF has variousapplications, for example in multi-agent pickup and delivery problems wheresome objects might require multiple agents to collaboratively pickup and movethem in unison. Precedence constraints also arise in warehouse assemblyproblems where before a manufacturing task can begin, its input resources mustbe manufactured and delivered. We propose a novel algorithm, PrecedenceConstrained Conflict Based Search (PC-CBS), which finds makespan-optimalsolutions for this class of problems. PC-CBS utilizes a Precedence-ConstrainedTask-Graph to define valid intervals for each planning task and updates themwhen precedence conflicts are encountered. We benchmark the performance of thisalgorithm over various warehouse assembly, and multi-agent pickup and deliverytasks, and use it to evaluate the sub-optimality of a recently proposedefficient baseline.

Optimal Multi-Agent Path Finding for Precedence Constrained Planning Tasks