Flocking Control Algorithms Based on the Diffusion Model for Unmanned Aerial Vehicle Systems
Ming Chen, Hanlu Chu, Xianglin Wei
Abstract
Flock is a desired state of unmanned aerial vehicle (UAV) systems, where multiple UAVs collaborate with each other in energy-efficient ways to complete mission-critical tasks while avoiding mutual collision. However, existing flocking control models still have defects such as potential node collision between followers, lack of capacity analysis, and difficulty in implementation. In this backdrop, this paper presents a model, called the diffusion model, to characterize the flock generation process of a UAV system; moreover, the system capacity of the diffusion model is analyzed. Then, a flocking control algorithm based on the diffusion model is detailed. Finally, a series of experiments based on both the OMNeT++ platform and a heterogeneous UAV-based prototype system are conducted to verify the effectiveness of our proposal. The experimental results show that our flocking control algorithm based on the diffusion model can make the UAV system behave as a flock while avoiding collision under diverse parameter settings.