The Multi-Agent Path Finding (MAPF) problem involves planning collision-free
paths for multiple agents in a shared environment. The majority of MAPF solvers
rely on the assumption that an agent can arrive at a specific location at a
specific timestep. However, real-world execution uncertainties can cause agents
to deviate from this assumption, leading to collisions and deadlocks. Prior
research solves this problem by having agents follow a Temporal Plan Graph
(TPG), enforcing a consistent passing order at every location as defined in the
MAPF plan. However, we show that TPGs are overly strict because, in some
circumstances, satisfying the passing order requires agents to wait
unnecessarily, leading to longer execution time. To overcome this issue, we
introduce a new graphical representation called a Bidirectional Temporal Plan
Graph (BTPG), which allows switching passing orders during execution to avoid
unnecessary waiting time. We design two anytime algorithms for constructing a
BTPG: BTPG-na\"ive and BTPG-optimized. Experimental results show that following
BTPGs consistently outperforms following TPGs, reducing unnecessary waits by
8-20%.Comment: Accepted by AAAI-202