3-D Path-Searching for Uavs Using Geographical Spatial Information
Chenchen Xu, Xiaohan Liao, Huanyin Yue, Xiaoming Deng, Xiwang Chen · 2019
Efficient path-planning is necessary to ensure safety and reliability for UAV's flights. However, existing path-searching algorithms are difficult to meet the high-efficiency-requirement for path planning in three-dimension situation. Therefore, this paper proposed a new three-dimensional path-planning method using improved Ant Colony Optimization (ACO) algorithm and fine hierarchical stratification. Firstly, we constructed a spatial gridding map for path-searching using grid discrete method based on high-precision geospatial data. Secondly, we searched for the optimal two-dimensional path on the minimum safe flight level for UAVs by improved algorithm. Lastly, paths were extended to three-dimensional space by introducing prominent mountains. To demonstrate the algorithm, we applied this method in a simulated environment established by MATLAB and compared outcomes with that of the traditional method. It is concluded that the method has higher convergence speed, better stability and higher computational efficiency.