An Optimal Control Approach to Flocking

TL;DR

This paper presents a decentralized optimal control framework for flocking that minimizes energy consumption and ensures safety, demonstrated through simulations in MATLAB and Gazebo.

Contribution

It introduces a novel optimal control approach for flocking that accounts for energy efficiency and safety in a decentralized manner.

Findings

Energy-efficient flocking achieved in simulations

Decentralized algorithm satisfies optimality and safety

Real-time implementation demonstrated in MATLAB and Gazebo

Abstract

Flocking behavior has attracted considerable attention in multi-agent systems. The structure of flocking has been predominantly studied through the application of artificial potential fields coupled with velocity consensus. These approaches, however, do not consider the energy cost of the agents during flocking, which is especially important in large-scale robot swarms. This paper introduces an optimal control framework to induce flocking in a group of agents. Guarantees of energy minimization and safety are provided, along with a decentralized algorithm that satisfies the optimality conditions and can be realized in real time. The efficacy of the proposed control algorithm is evaluated through simulation in both MATLAB and Gazebo.