Integer-Programming-Based Narrow-Passage Multi-Robot Path Planning with Effective Heuristics

TL;DR

This paper introduces OMRPP, an integer programming-based algorithm for multi-robot path planning in warehouse environments, featuring topological map extraction, one-way passage constraints, and a heuristic for feasible solutions, improving efficiency and collision avoidance.

Contribution

It presents a novel IP-based algorithm with environment-specific heuristics and constraints to enhance multi-robot path planning efficiency in warehouse-like settings.

Findings

The proposed method reduces planning cost in warehouse environments.

It ensures feasible initial solutions for the IP model.

Simulations show improved efficiency and collision avoidance.

Abstract

We study optimal Multi-robot Path Planning (MPP) on graphs, in order to improve the efficiency of multi-robot system (MRS) in the warehouse-like environment. We propose a novel algorithm, OMRPP (One-way Multi-robot Path Planning) based on Integer programming (IP) method. We focus on reducing the cost caused by a set of robots moving from their initial configuration to goal configuration in the warehouse-like environment. The novelty of this work includes: (1) proposing a topological map extraction based on the property of warehouse-like environment to reduce the scale of constructed IP model; (2) proposing one-way passage constraint to prevent the robots from having unsolvable collisions in the passage. (3) developing a heuristic architecture that IP model can always have feasible initial solution to ensure its solvability. Numerous simulations demonstrate the efficiency and performance of the proposed algorithm.