基于改进人工蜂群算法的无人机三维航迹规划

The UAV 3D Path Planning Based on Improved ABC Algorithm

为应对无人机遇到的复杂任务状况,提高航迹规划效率,提出一种基于改进人工蜂群算法的无人机三维航迹规划方法。为降低无人机三维航迹规划的难度,将航迹规划数学模型通过简化建模转化为函数优化问题;为提高航迹优化效率,通过改进蜜源初始化方式、引入动态评价选择策略、引入Metropolis准则等方式对传统人工蜂群算法在该问题求解中的缺陷进行改进,通过MATLAB进行20次仿真实验,验证了改进人工蜂群算法在无人机三维航迹规划中的可行性和优化效率。

In order to confront the complex tasks of Unmanned Aerial Vehicles(UAV)and improve path planning efficiency,a UAV flight 3D path planning method based on improved artificial bee colony(ABC)algorithm was put forward.In order to reduce the difficulty of UAV 3D path planning,mathematical models of path planning are transformed into function optimization problems by simplifying the model.To increase path planning efficiency,limitations of traditional ABC algorithm are improved by improving the way of initialization nectar source,introduction of dynamic evaluation selection strategy,introduction of metropolis rule,etc.The improved ABC algorithm′s feasibility and optimizing efficiency on UAV 3D path planning are verified by 20 MATLAB simulation experiments.