A Distributed Version of the Hungarian Method for Multi-Robot Assignment

TL;DR

This paper introduces a distributed Hungarian Method enabling multi-robot teams to collaboratively solve assignment and routing problems efficiently through local computations and peer-to-peer communication, demonstrated via a multi-robot musical performance.

Contribution

It presents a novel distributed algorithm for the assignment problem tailored for multi-robot systems, including applications with spatio-temporal constraints and online route optimization.

Findings

Robust distributed algorithm for multi-robot assignment.

Successful online, suboptimal routing in dynamic settings.

Experimental validation with robotic orchestral performance.

Abstract

In this paper, we propose a distributed version of the Hungarian Method to solve the well known assignment problem. In the context of multi-robot applications, all robots cooperatively compute a common assignment that optimizes a given global criterion (e.g. the total distance traveled) within a finite set of local computations and communications over a peer-to-peer network. As a motivating application, we consider a class of multi-robot routing problems with "spatio-temporal" constraints, i.e. spatial targets that require servicing at particular time instants. As a means of demonstrating the theory developed in this paper, the robots cooperatively find online, suboptimal routes by applying an iterative version of the proposed algorithm, in a distributed and dynamic setting. As a concrete experimental test-bed, we provide an interactive "multi-robot orchestral" framework in which a team of robots cooperatively plays a piece of music on a so-called orchestral floor.