MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problem

Fuente: arXiv
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Main Authors: Tang, Mingkai, Li, Yuanhang, Liu, Hongji, Chen, Yingbing, Liu, Ming, Wang, Lujia
Format: Preprint
Published: 2024
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_version_ 1866910428731277312
author Tang, Mingkai
Li, Yuanhang
Liu, Hongji
Chen, Yingbing
Liu, Ming
Wang, Lujia
author_facet Tang, Mingkai
Li, Yuanhang
Liu, Hongji
Chen, Yingbing
Liu, Ming
Wang, Lujia
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2404_19518
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problem
Tang, Mingkai
Li, Yuanhang
Liu, Hongji
Chen, Yingbing
Liu, Ming
Wang, Lujia
Multiagent Systems
Artificial Intelligence
Robotics
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.
title MGCBS: An Optimal and Efficient Algorithm for Solving Multi-Goal Multi-Agent Path Finding Problem
topic Multiagent Systems
Artificial Intelligence
Robotics
url https://arxiv.org/abs/2404.19518