Optimal Control Techniques for Heterogeneous UAV Swarms

Abstract

Heterogeneous Unmanned Aerial Vehicle (UAV) swarms offer unique opportunities for solving multi-robot missions, but also introduce novel implementation challenges. In our study, we develop Heterogeneous Decentralized Receding Horizon Control (HD-RHC) for swarm management in search & rescue missions. This new technique builds upon existing multiagent UAV work, but adds the capacity to manage a fleet of heterogeneous, diverse robot platforms that are equipped for different mission capabilities. Through high-fidelity simulation (AirSim), we derive an optimal controller, develop a method to find optimal weights for a specific mission focus, and provide a path to physical system validation. We analyze the efficiency and performance of HD-RHC controller, and discuss different ways this new method can be integrated into mission-management scenarios.