平滑改进A*算法在无人机航迹规划中的应用

Application of smooth improved A-star algorithm in UAV flight path planning

传统的A*算法易于陷入局部极小,搜索速度较慢,规划的路径有较多折线。文章对传统A*算法进行了两个改进,并将其应用于无人机航迹规划。一是在代价函数中加入无人机的转向代价估计,稳定其飞行方向;二是采用后处理方法对航迹点进行拟合,获得平滑的最短路径曲线。为保证拟合后的路径不会出现较大波动,拟合过程没有使用所有的航迹点,而是在一定的误差允许范围内选取特征点进行拟合。改进算法的有效性通过仿真和实验予以验证。

Traditional A-star algorithm spends much time on searching optimal solution, and is easy to fall into local minima.Moreover, the planned path contains many polygonal lines. In this paper, two improvements are made to the traditional A-star algorithm, and it is applied to the path planning of UAV. One is to add the UAV steering cost estimation to the distance cost function to stabilize its flight direction;the other is to use the post processing method to fit the track points to obtain the smooth shortest path curve. In order to ensure that the fitted path will not fluctuate greatly, the fitting process does not use all the track points, but selects the feature points for fitting within a certain range of allowable error. The effectiveness of the improved algorithm is verified by simulation and experiment.