基于混合蚁群算法的无人机航迹规划

UAV path planning based on hybrid ant colony algorithm

由于传统方法在无人机航迹规划实际应用中规划的航迹长度较长,文章提出基于混合蚁群算法的无人机航迹规划。由山峰模型和天气模型组建无人机航迹环境数学模型,描述无人机飞行航迹环境情况,以无人机航迹代价最小建立目标函数,并对无人机航迹长度、高度、速度、转弯角度进行约束,采用混合蚁群算法对目标函数求解,求出最优航迹规划策略。实验证明,文章设计方法规划的航迹长度最短为1032.58 m,规划航迹长度较短,在无人机航迹规划方面具有良好的应用前景。

Due to the long flight path length planned by traditional methods in the practical application of UAV flight path planning,this paper proposes a UAV flight path planning method based on hybrid ant colony algorithm.A mathematical model of UAV’s flight path environment was established by mountain peak model and weather model to describe the environment of UAV’s flight path.The objective function was established with the minimum cost of UAV’s flight path,and constraints were set according to the actual requirements to constrain the length,height,speed and turning Angle of UAV’s flight path.The mixed ant colony algorithm was used to solve the objective function,and the optimal flight path planning strategy was obtained.The experimental results show that the shortest length of the planned flight path is 1032.58 m,and the planned flight path length is relatively short,which has a good application prospect in UAV flight path planning.