DMS*: Minimizing Makespan for Multi-Agent Combinatorial Path Finding

TL;DR

This paper introduces DMS*, a novel algorithm for multi-agent path finding that minimizes the maximum arrival time (makespan) by deferring target sequencing, enabling efficient planning for many agents and targets.

Contribution

It proposes DMS*, a new method that extends MS* to minimize makespan in multi-agent path finding by delaying target sequencing, improving computational efficiency.

Findings

DMS* effectively minimizes makespan in multi-agent scenarios.

DMS* scales to 20 agents and 80 targets in experiments.

Demonstrated applicability on differential-drive robots.

Abstract

Multi-Agent Combinatorial Path Finding (MCPF) seeks collision-free paths for multiple agents from their initial to goal locations, while visiting a set of intermediate target locations in the middle of the paths. MCPF is challenging as it involves both planning collision-free paths for multiple agents and target sequencing, i.e., solving traveling salesman problems to assign targets to and find the visiting order for the agents. Recent work develops methods to address MCPF while minimizing the sum of individual arrival times at goals. Such a problem formulation may result in paths with different arrival times and lead to a long makespan, the maximum arrival time, among the agents. This paper proposes a min-max variant of MCPF, denoted as MCPF-max, that minimizes the makespan of the agents. While the existing methods (such as MS*) for MCPF can be adapted to solve MCPF-max, we further develop two new techniques based on MS* to defer the expensive target sequencing during planning to expedite the overall computation. We analyze the properties of the resulting algorithm Deferred MS* (DMS*), and test DMS* with up to 20 agents and 80 targets. We demonstrate the use of DMS* on differential-drive robots.