Cooperative Control of Physical Collision and Transmission Power for UAV Swarm: A Dual-Fields Enabled Approach
Wenjun Xu, Lanhua Xiang, Tiankui Zhang, Miao Pan, Zhu Han
Abstract
This article studies the collision avoidance and interference mitigation for unmanned aerial vehicle (UAV) swarm where many UAVs track a common target. The considered problem is formulated to jointly minimize the average interference and ensure the collision avoidance among UAVs. By exploiting the problem characteristics, our major contributions are summarized as follows. First, the singular case tolerance (SCT)-artificial potential field (APF) is proposed to overcome the failure of traditional APFs in collision avoidance, where the repulsive force gain coefficient among UAVs is dynamically controlled by the corresponding interferences. Second, the mean-field game (MFG) model is established to control communication power, where the instantaneous interferences among flying UAVs are represented by the mean-field approximation. Third, considering the tight coupling of trajectory and interference of UAVs, a cooperative control approach enabled by dual-fields is proposed to jointly adjust the trajectories and power of UAVs. Simulation results validate the significant performance improvement of the cooperative control approach enabled by dual-fields. Compared with separate APF and MFG, the proposed dual-field-cooperation approach can achieve about 117% throughput gain and 88% interference reduction when the UAV swarm is close to the target.