【摘要】 为了实现基于预设航线的无人机三维避障,提高无人机(UAV)的自主能力,提出一种改进型人工势场算法。传统的人工势场法避障只着眼于无人机的安全到达,且可能会陷入局部最小点。当避障基于预设航线时,传统人工势场无法在避障的同时尽量跟踪预设航线,对传统人工势场引力场进行改进,使引力指向目标航线,并针对预设航线为曲线时引入前馈和速度控制,消除跟踪误差;为解决引力场改进后人工势场法存在局部最小点问题,对斥力场进行改进,使其垂直于航线方向,消除局部最小点。将改进后的算法运用到近地表自主搜索无人机的三维避障中,将三维避障分解为XY和XZ 2个平面上的避障,在Adams上构建避障场景进行仿真,仿真结果显示该算法能够实现基于预设航线的无人机三维避障,且避障过程平稳。更多还原

【Abstract】 To realize the three-dimensional obstacle avoidance of unmanned aerial vehicles(UAVs) based on preset routes and improve the autonomous capabilities of drones, an improved artificial potential field algorithm is proposed. The traditional artificial potential field method only focuses on the safe arrival of UAVs and may fall into a local minimum. When the obstacle avoidance is based on a preset route, the traditional artificial potential field cannot track the preset route while avoiding obstacles, so it is improved, specifically to make the gravitational force point to the target route. Feed-forward and speed control are introduced to eliminate the tracking error when the route is a curve. In order to solve the problem of local minimum point of the artificial potential field method after the improvement of the gravitational field, the repulsive force field is improved to be opposite to the direction of route and eliminate the local minimum point. The improved algorithm is applied to the three-dimensional obstacle avoidance of drones. In order to verify the performance of the proposed algorithm, obstacle avoidance scenarios are constructed on Adams to simulate the obstacles in three dimensions, and the simulation results show that the proposed algorithm can realize the three-dimensional obstacle avoidance of UAVs based on the preset routes, and the obstacle avoidance process is stable.更多还原