Swarm Mode Design and Hybrid Flocking Control Algorithm for Swarm Operation of Small Fixed-wing UAVs

This paper presents a swarm system for small fixed-wing unmanned aerial vehicles (UAVs). To enable multiple UAVs to perform various missions while maintaining close proximity and avoiding collisions, we develop a hybrid-flocking control algorithm that combines three types of control protocols: vector field guidance for path following and loitering, the augmented Cucker Smale model for collective flocking behavior, and a potential field for collision avoidance. Additionally, to address the requirements of different mission scenarios, we define several swarm modes: swarm collective loitering for cohesive circling at the same altitude, swarm group loitering for circling at different altitudes, swarm movement for flocking flight toward a target point, and individual loitering for single UAV circling. To reduce the risk of collisions during mode transitions, we employ k-means clustering to form subgroups and optimize control weights within the hybrid-flocking control algorithm. The effectiveness of the proposed system is validated through simulations of swarm mission scenarios. These simulations demonstrate that missions can be performed safely without collisions by utilizing optimized weights for the various swarm modes.