基于改进人工势场法的动态环境下无人机路径规划

基于传统人工势场法,在相对位置引力场和斥力场函数中分别引入目标与障碍物的速度矢量,将其位置动态变化信息融入在改进后的相对速度引力场和斥力场中,引入相对位置引力、相对速度引力、相对位置斥力、相对速度斥力等比例调节因子,建立改进后的人工势场函数及多障碍物合力函数,并在模拟环境下进行仿真。结果表明,该改进人工势场法能满足无人机在目标与障碍物动态变化条件下的路径规划的安全性、实时性和可达性,并提高了动态环境中无人机的跟踪与避障速度。

UAV path planning based on improved artificial potential field in dynamic environment

Based on the traditional artificial potential field method, the velocity vector of the targets and obstacles were introduced into the relative position gravitational field and repulsion field function. The information of dynamic changing position was integrated into the improved relative velocity gravitational field and repulsion field. The relative position of gravity, the relative position and speed of repulsion, and other proportional adjustment factors were introduced. The improved artificial potential field function and multi-obstacle force function were established to simulate in the simulation environment. The results show that the improved artificial potential field method can not only meet the requirements of safety, real-time capability and reachability of UAV path planning under the dynamic changes of targets and obstacles, but also improves the tracking and obstacle avoidance speed of the UAV in a dynamic environment.