Multi-Agent Path Finding Algorithm Based on Bounded Suboptimal Search in Complex Terrain

In the multi-agent path finding problem, the conflict between agents in the complex terrain will not only reduce the quality of the solution, but also consume a lot of computing resources. This situation has led to many large-scale multi-agent path finding problems that are difficult to solve in a given time. To solve this difficulty, a multi-agent path finding algorithm based on bounded suboptimal search is proposed in this paper. The algorithm lists the common complex terrain and gives the recognition method. For agent with cardinal conflict in complex terrain, the algorithm provides relaxation for its suboptimal upper bounds, which allows the final solution to appear earlier in the search space, thus reducing the computation time. It is worth mentioning that although the cost of some agents exceeds the suboptimal upper bound, it can be guaranteed that the sum of cost remains within the suboptimal upper bound. Finally, it is proved through experiments that the algorithm proposed in this paper significantly improves the efficiency of the solution compared to existing algorithms.