Multi-Agent Corridor Generating Algorithm

TL;DR

This paper introduces MACGA, a novel multi-agent pathfinding algorithm that constructs corridors to efficiently find collision-free paths, and enhances it with PIBT for better performance, demonstrating superior results on benchmark grids.

Contribution

The paper presents MACGA, a new corridor-based algorithm for MAPF, and integrates PIBT to improve runtime and solution quality, with proven polynomial-time guarantees.

Findings

MACGA outperforms baseline algorithms in success rate and runtime.

MACGA+PIBT improves solution quality and efficiency.

Algorithms guarantee reachability for all agents.

Abstract

In this paper, we propose the Multi-Agent Corridor Generating Algorithm (MACGA) for solving the Multi-agent Pathfinding (MAPF) problem, where a group of agents need to find non-colliding paths to their target locations. Existing approaches struggle to solve dense MAPF instances. In MACGA, the agents build \emph{corridors}, which are sequences of connected vertices, from current locations towards agents' goals, and evacuate other agents out of the corridors to avoid collisions and deadlocks. We also present the MACGA+PIBT algorithm, which integrates the well-known rule-based PIBT algorithm into MACGA to improve runtime and solution quality. The proposed algorithms run in polynomial time and have a reachability property, i.e., every agent is guaranteed to reach its goal location at some point. We demonstrate experimentally that MACGA and MACGA+PIBT outperform baseline algorithms in terms of success rate, runtime, and makespan across diverse MAPF benchmark grids.