Behavioral-based circular formation control for robot swarms

TL;DR

This paper presents a novel decentralized formation control algorithm for robot swarms that enables collision-free orbiting around convex paths, inspired by tornado schooling fish, using local information and adaptive safety measures.

Contribution

It introduces a scalable, collision-free formation control method combining overtaking rules, vector fields, and control barrier functions, with rigorous analysis and simulation validation.

Findings

Effective collision avoidance in dense swarms

Successful orbiting around convex paths

Distributed decision-making with local info

Abstract

This paper focuses on coordinating a robot swarm orbiting a convex path without collisions among the individuals. The individual robots lack braking capabilities and can only adjust their courses while maintaining their constant but different speeds. Instead of controlling the spatial relations between the robots, our formation control algorithm aims to deploy a dense robot swarm that mimics the behavior of tornado schooling fish. To achieve this objective safely, we employ a combination of a scalable overtaking rule, a guiding vector field, and a control barrier function with an adaptive radius to facilitate smooth overtakes. The decision-making process of the robots is distributed, relying only on local information. Practical applications include defensive structures or escorting missions with the added resiliency of a swarm without a centralized command. We provide a rigorous analysis of the proposed strategy and validate its effectiveness through numerical simulations involving a high density of unicycles.