Distributed Autonomous Formation Tracking for UAV Swarm in Complex Environments
Fan Yang, Qiang Lu, Mo Chen, Jianxiao Lin, Botao Zhang · 2025
In this paper, a distributed autonomous formation tracking method for unmanned aerial vehicle (UAV) swarm is proposed, aiming to improve swarm's target tracking capability in complex environments. First, the collision adjustment region is designed, which enables UAVs to fly safely and efficiently under lightweight local neighborhood communication condition, and overcomes the limitation of traditional swarm control on global information dependence. Second, an autonomous formation approach under local neighborhood communication method is proposed. The target position for each UAV is determined by offset relative to formation center in conjunction with the average of positions from all UAVs, dynamically determining target position without the requirement for a preset fixed position. This policy provides flexible formation and effectively reduces the collision risk. Finally, the above method is combined with obstacle avoidance capability, solving the problem of real-time dynamic target tracking in complex environments. Simulation results validate that UAVs can effectively track dynamic target in complex environments.