Cooperative Object Transportation using Gibbs Random Fields

TL;DR

This paper introduces a decentralized method for swarm robots to cooperatively transport objects by modeling their interactions as a Gibbs Random Field, enabling emergent behaviors without explicit communication.

Contribution

The paper presents a novel application of Gibbs Random Fields to enable decentralized, emergent cooperative transportation in robot swarms.

Findings

Method is scalable and adaptable

Robust to failures and environmental changes

Effective in simulations and experiments

Abstract

This paper presents a novel methodology that allows a swarm of robots to perform a cooperative transportation task. Our approach consists of modeling the swarm as a {\em Gibbs Random Field} (GRF), taking advantage of this framework's locality properties. By setting appropriate potential functions, robots can dynamically navigate, form groups, and perform cooperative transportation in a completely decentralized fashion. Moreover, these behaviors emerge from the local interactions without the need for explicit communication or coordination. To evaluate our methodology, we perform a series of simulations and proof-of-concept experiments in different scenarios. Our results show that the method is scalable, adaptable, and robust to failures and changes in the environment.