Distributed Camouflage for Swarm Robotics and Smart Materials

TL;DR

This paper introduces a distributed algorithm enabling a swarm of active particles to autonomously adapt their camouflage patterns to various environments, inspired by cuttlefish, with proven convergence in simulation and real robot experiments.

Contribution

It presents a novel distributed estimation and pattern formation algorithm for swarm robotics, allowing dynamic camouflage adaptation inspired by biological systems.

Findings

Algorithm achieves rapid environmental adaptation.

Convergence demonstrated in simulation and physical robot swarm.

Effective in forming diverse camouflage patterns.

Abstract

We present a distributed algorithm for a swarm of active particles to camouflage in an environment. Each particle is equipped with sensing, computation and communication, allowing the system to take color and gradient information from the environment and self-organize into an appropriate pattern. Current artificial camouflage systems are either limited to static patterns, which are adapted for specific environments, or rely on back-projection, which depend on the viewer's point of view. Inspired by the camouflage abilities of the cuttlefish, we propose a distributed estimation and pattern formation algorithm that allows to quickly adapt to different environments. We present convergence results both in simulation as well as on a swarm of miniature robots "Droplets" for a variety of patterns.