基于时空数据挖掘的无人机航线自动寻优规划

Automatic route optimization planning of UAV based on spatio temporal data mining

为了解决无人机航线规划安全越障问题,提出基于时空数据挖掘的无人机航线自动寻优规划方法研究。采用线性插值方法补全缺失航线数据,完成航线数据预处理;划分航线集的时间尺度与空间尺度,通过矩阵分解处理提取时空特征;应用蚁群算法制定航线规划程序,实现无人机航线的自动寻优规划。测试结果表明,应用提出方法获得的时空数据挖掘深度系数平均值分别为9.05与8.91,无人机航线寻优规划收敛速度较快,可安全避开所有障碍,解决复杂环境下无人机航线规划安全越障问题。

In order to solve the problem of safe obstacle crossing in UAV route planning,an automatic optimization method for UAV route planning based on spatio-temporal data mining is proposed.The linear interpolation method is used to complete the missing route data and complete the route data pre-processing;Divide the time scale and space scale of the route set,and extract the spatio-temporal characteristics through matrix decomposition.The ant colony algorithm is applied to develop the route planning program to realize the automatic optimization planning of UAV route.The test results show that the average values of the depth coefficients of spatio-temporal data mining obtained by the proposed method are 9.05 and 8.91 respectively.The UAV route optimization planning converges faster,safely avoids all obstacles,and solves the problem of safe obstacle crossing of UAV route planning in complex environments.