Distributed Cohesive Control for Robot Swarms: Maintaining Good Connectivity in the Presence of Exterior Forces

TL;DR

This paper introduces local control algorithms for robot swarms that maintain connectivity and robustness against external forces and failures, inspired by Euclidean Steiner trees, ensuring scalable and resilient collective behavior.

Contribution

It presents a novel set of local continuous algorithms that generalize Euclidean Steiner trees for robust, scalable, and flexible swarm connectivity under external disturbances.

Findings

Scales well with swarm size

Robust against node failures

Performs near optimal in connectivity maintenance

Abstract

We present a number of powerful local mechanisms for maintaining a dynamic swarm of robots with limited capabilities and information, in the presence of external forces and permanent node failures. We propose a set of local continuous algorithms that together produce a generalization of a Euclidean Steiner tree. At any stage, the resulting overall shape achieves a good compromise between local thickness, global connectivity, and flexibility to further continuous motion of the terminals. The resulting swarm behavior scales well, is robust against node failures, and performs close to the best known approximation bound for a corresponding centralized static optimization problem.