Optimal Transport-based Coverage Control for Swarm Robot Systems: Generalization of the Voronoi Tessellation-based Method

TL;DR

This paper introduces an optimal transport-based coverage control method for swarm robots, improving distribution accuracy and encompassing existing methods as special cases, with proven stability and superior performance.

Contribution

It formulates a novel coverage control paradigm using optimal transport theory, generalizing and enhancing existing Voronoi-based methods.

Findings

OTCC reproduces target distributions more accurately.

The method demonstrates better performance than existing control techniques.

Lyapunov stability of the system is established.

Abstract

Swarm robot systems, which consist of many cooperating mobile robots, have attracted attention for their environmental adaptability and fault tolerance advantages. One of the most important tasks for such systems is coverage control, in which robots autonomously deploy to approximate a given spatial distribution. In this study, we formulate a coverage control paradigm using the concept of optimal transport and propose a novel control technique, which we have termed the optimal transport-based coverage control (OTCC) method. The proposed OTCC, derived via the gradient flow of the cost function in the Kantorovich dual problem, is shown to covers a widely used existing control method as a special case. We also perform a Lyapunov stability analysis of the controlled system, and provide numerical calculations to show that the OTCC reproduces target distributions with better performance than the existing control method.