Cooperative Pathfinding Based on Memory-Efficient Multi-Agent RRT*

• Main Authors: Jinmingwu Jiang, Kaigui Wu
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Cooperative pathfinding; collision avoidance; multi-agent motion planning; path planning
• Online Access: https://ieeexplore.ieee.org/document/9194248/

In cooperative pathfinding problems, non-conflict paths that bring several agents from their start location to their destination need to be planned. This problem can be efficiently solved by Multi-agent RRT*(MA-RRT*) algorithm, which is still state-of-the-art in the field of coupled methods. However, the implementation of this algorithm is hindered in systems with limited memory because the number of nodes in the tree of RRT* grows indefinitely as the paths get optimized. This paper proposes an improved version of MA-RRT*, called Multi-agent RRT* Fixed Node(MA-RRT*FN), which limits the number of nodes stored in the tree of RRT* by removing the weak nodes on the path which are not likely to reach the goal. The results show that MA-RRT*FN performs close to MA-RRT* in terms of scalability and solution quality while the memory required is much lower and fixed.