基于自适应粒子群算法的多无人机混合编队技术

Multi-UAV hybrid formation technology based on Adaptive Particle Swarm Optimization

摘要:

为了解决无人机群体在复杂战场环境下的编队、避障、避碰问题，提出了一种将基于行为法和虚拟领航者法相结合的混合编队技术。为无人机编队设计了奔向目标、队形保持、避碰、避障四种基本行为，通过对编队无人机的行为权重参数进行调整控制无人机编队的机动，编队无人机的行为权重参数通过自适应粒子群算法进行优化，然后对编队无人机的基本行为进行矢量合成，归一化处理后控制无人机的机动。仿真实验测试证明了该方法能使无人机群体保持期望的队形，实现了编队避障和内部避碰，进而更有效地完成编队任务，提高了多无人机编队的机动性能，促进了多无人机混合技术的发展。

Abstract:

The article combines the behavior-based method and the virtual pilot approach and proposes a new UAV hybrid formation technology to solve the problems of multi-UAVs in complex battlefield environment, such as the formation, obstacle avoidance and collision avoidance. Four basic behaviors are designed for UAV formation, which are running to the target, keeping formation, avoiding collision and avoiding obstacles. By adjusting the behavior weight parameters of UAV formation, the maneuver of UAV formation is controlled. The adaptive particle swarm optimization algorithm is applied to optimize the behavior weight parameters, then the basic behavior of the formation UAV is vector synthesized. And then control the maneuvering of the drone after normalization. Simulation experiment results show that this method can make the UAV group complete the tasks of formation more effectively. Besides this method improves the maneuverability of multi-UAV formation and promotes the development of multi-UAV hybrid formation technology.