With the expansion of the scale of robotics applications, the multi-goal multi-agent pathfinding (MG-MAPF) problem began to gain widespread attention. This problem requires each agent to visit pre-assigned multiple goal points at least once without conflict. Some previous methods have been proposed to solve the MG-MAPF problem based on Decoupling the goal Vertex visiting order search and the Single-agent pathfinding (DVS). However, this paper demonstrates that the methods based on DVS cannot always obtain the optimal solution. To obtain the optimal result, we propose the Multi-Goal Conflict-Based Search (MGCBS), which is based on Decoupling the goal Safe interval visiting order search and the Single-agent pathfinding (DSS). Additionally, we present the Time-Interval-Space Forest (TIS Forest) to enhance the efficiency of MGCBS by maintaining the shortest paths from any start point at any start time step to each safe interval at the goal points. The experiment demonstrates that our method can consistently obtain optimal results and execute up to 7 times faster than the state-of-the-art method in our evaluation.

翻译：随着机器人应用规模的扩大，多目标多智能体路径规划（MG-MAPF）问题开始受到广泛关注。该问题要求每个智能体在无冲突的情况下至少访问一次预分配的多个目标点。此前已有方法基于解耦目标顶点访问顺序搜索与单智能体路径规划（DVS）来解决MG-MAPF问题。然而，本文证明基于DVS的方法并非总能获得最优解。为获得最优结果，我们提出多目标冲突搜索（MGCBS）算法，其基于解耦目标安全间隔访问顺序搜索与单智能体路径规划（DSS）。此外，我们引入时间间隔空间森林（TIS Forest）结构，通过维护从任意起始点、任意起始时间步到各目标点安全间隔的最短路径，提升MGCBS的效率。实验表明，我们的方法能够稳定获得最优解，且在我们的评估中执行速度比现有最优方法快达7倍。