Decentralized Control of Minimalistic Robotic Swarms For Guaranteed Target Encapsulation

TL;DR

This paper presents a decentralized control algorithm enabling minimalistic robotic swarms to reliably search for and encapsulate targets while avoiding obstacles, despite individual robots having no memory or localization capabilities.

Contribution

It introduces a novel decentralized control method that guarantees complex swarm behaviors with robots lacking memory, localization, or knowledge of neighbors' positions.

Findings

Swarm behavior is robust to sensor noise and asynchronous execution.

The control algorithm guarantees target encapsulation and obstacle avoidance.

Emergent behavior varies predictably with task parameters.

Abstract

We propose a decentralized control algorithm for a minimalistic robotic swarm with limited capabilities such that the desired global behavior emerges. We consider the problem of searching for and encapsulating various targets present in the environment while avoiding collisions with both static and dynamic obstacles. The novelty of this work is the guaranteed generation of desired complex swarm behavior with constrained individual robots which have no memory, no localization, and no knowledge of the exact relative locations of their neighbors. Moreover, we analyze how the emergent behavior changes with different parameters of the task, noise in the sensor reading, and asynchronous execution.