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The Multi-Agent Path Finding (MAPF) problem involves planning collision-freepaths for multiple agents in a shared environment. The majority of MAPF solversrely on the assumption that an agent can arrive at a specific location at aspecific timestep. However, real-world execution uncertainties can cause agentsto deviate from this assumption, leading to collisions and deadlocks. Priorresearch solves this problem by having agents follow a Temporal Plan Graph(TPG), enforcing a consistent passing order at every location as defined in theMAPF plan. However, we show that TPGs are overly strict because, in somecircumstances, satisfying the passing order requires agents to waitunnecessarily, leading to longer execution time. To overcome this issue, weintroduce a new graphical representation called a Bidirectional Temporal PlanGraph (BTPG), which allows switching passing orders during execution to avoidunnecessary waiting time. We design two anytime algorithms for constructing aBTPG: BTPG-na\"ive and BTPG-optimized. Experimental results show that followingBTPGs consistently outperforms following TPGs, reducing unnecessary waits by8-20%.

Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution