Cooperative Pathfinding based on memory-efficient Multi-agent RRT*

TL;DR

This paper introduces MA-RRT*FN, an improved multi-agent pathfinding algorithm that limits memory usage by removing weak nodes, maintaining solution quality and scalability in memory-constrained systems.

Contribution

It proposes a memory-efficient version of MA-RRT* that fixes node count, enabling practical application in systems with limited memory.

Findings

MA-RRT*FN reduces memory usage significantly.

Solution quality remains comparable to original MA-RRT*.

Scalability is maintained despite memory constraints.

Abstract

In cooperative pathfinding problems, no-conflicts 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 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 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.