Distributed Formation Control and Collision Avoidance for Heterogeneous UAV Swarm

This paper proposes a formation and collision avoidance method for heterogeneous swarm consisting of Unmanned Aerial Vehicles (UAVs) with variable detection abilities. First of all, preliminary knowledge such as the kinematic model of UAV and Particle Swarm Optimization (PSO) algorithm is introduced. Then, the proposed method based on Distributed Model Predictive Control (DMPC) is expressed in detail by dividing UAVs into heterogeneous roles and designing cost functions for different roles according to task requirements. A coordination strategy is further proposed to dissolve the conflict between formation maintenance and collision avoidance. Numerical simulations further demonstrate that the method effectively applies to the formation and collision avoidance task of heterogeneous UAV swarm. Finally, further research direction and potential improvements are discussed.