UAV swarm track planning is crucial to ensure the smooth completion of the complex assigned tasks. UAV formation is of great significance to UAV swarm track planning. At present, UAV formation control methods have the defects of only set one formation type in the whole process, and poor adaptability in complex environment. This paper incorporates the formation decision function into the UAV control mode of virtual point formation, and classifies it at the expected angle based on the track planning model of pigeon swarm behavior, and puts forward a hierarchical early warning mechanism. In simulation experiment the method proposed in this paper can make UAV adjust its formation according to the environment, and avoid collisions between UAVs and various obstacles. In the adaptability of the algorithm, we fully consider the addition and deletions of UAV, static and dynamic obstacles, the interference of wind phenomenon and the diversity of tasks in the actual environment. The method proposed in this paper has made a beneficial attempt in the field of UAV control and expanded the application of UAV swarm.

无人机群的轨道规划对于确保顺利完成复杂的分配任务至关重要。无人机编队对无人机群轨迹规划具有重要意义。目前，无人机编队控制方法在全过程中只设置一种编队类型的缺陷，在复杂环境下的适应性较差。本文将编队决策功能纳入虚拟点编队的无人机控制模式，并基于鸽子群行为的航迹规划模型，以期望角度对编队决策函数进行分类，提出了分层预警机制。在仿真实验中，本文提出的方法可以使无人机根据环境调整其形态，避免无人机与各种障碍物发生碰撞。在算法的适应性上，我们充分考虑了无人机的添加和删除，静态和动态障碍物，风现象的干扰以及实际环境中任务的多样性。本文提出的方法在无人机控制领域进行了有益的尝试，扩大了无人机群的应用范围。