This paper proposes a novel two-layer framework based on conflict-based search and regional divisions to improve the efficiency of multi-robot path planning. The high-level layer targets the reduction of conflicts and deadlocks, while the low-level layer is responsible for actual path planning. Distinct from previous dual-level search frameworks, the novelties of this work are (1) subdivision of planning regions for each robot to decrease the number of conflicts encountered during planning; (2) consideration of the number of robots in the region during planning in the node expansion stage of A*, and (3) formal proof demonstrating the nonzero probability of the proposed method in obtaining a solution, along with providing the upper bound of the solution in a special case. Experimental comparisons with Enhanced Conflict-Based Search demonstrate that the proposed method not only reduces the number of conflicts but also achieves a computation time reduction of over 30%.
