''It Is Much Safer to Be Sparse than Connected'': Safe Control of Robotic Swarm Density Dynamics with PDE-Optimization with State Constraints

TL;DR

This paper presents a control strategy for robotic swarms that ensures safety by guiding their density distribution using PDE-based optimization, with proven guarantees and real-world validation.

Contribution

It introduces a novel closed-loop control method utilizing Lyapunov and barrier functions for safe swarm density regulation, including a distributed Voronoi-based variant.

Findings

Sparse swarms are easier to keep safe than dense ones.

The proposed controllers are validated through simulations and real-world experiments.

The approach guarantees safety under localization and motion noise conditions.

Abstract

This paper introduces a safety-critical optimization-based control strategy that leverages control Lyapunov and control barrier functions to guide the spatial density of robotic swarms governed by the Fokker-Planck equation to a predefined target distribution. In contrast to traditional open-loop state-constrained optimal control strategies, the proposed approach operates in closed-loop, and a Voronoi-based variant further enables distributed deployments. Theoretical guarantees of safety are derived, and numerical simulations demonstrate the performance of the proposed controllers. Finally, a multi-robot experiment showcases the real-world applicability of the proposed controllers under localization and motion noises, illustrating how it is much easier for a sparse swarm to satisfy safety specifications than it is for a densely packed one.