An Optimal Control Approach to Flocking
arXiv:1909.12330 · doi:10.23919/ACC45564.2020.9147311
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.
6 pages, 4 figures. To appear at the 2020 American Control Conference
References in corpus (4)
- A Decentralized Energy-Optimal Control Framework for Connected Automated Vehicles at Signal-Free Intersections
- A Duality Framework for Stochastic Optimal Control of Complex Systems
- An Energy-Optimal Framework for Assignment and Trajectory Generation in Teams of Autonomous Agents
- A Decentralized Control Framework for Energy-Optimal Goal Assignment and Trajectory Generation