一种基于Voronoi图的航路规划方法

A Path Planning Method Based on Voronoi Diagram

Voronoi图是一种根据战场多威胁源分布情况获取可行航路点的图形算法,而蚁群算法是一种新型的模拟进化启发式算法。提出一种基于Voronoi图算法的无人机航路规划解决方法,提升了在多威胁源分布的情况下的无人机航路规划效率。首先,根据已知威胁源的数据信息生成加权Voronoi图,并定义每条Voronoi边的代价为组成Voronoi边的2个端点的直线距离;然后利用蚁群算法结合可飞行航迹点集合对无人机在多威胁源分布的飞行环境下进行航路规划。仿真结果验证了所提方法在不同战场环境下解决无人机航路规划问题上的可行性和有效性。

Voronoi diagram is a diagram algorithm fetching optimal path points according to the dis- tribution status of multiple threat sources in battlefield. Ant colony algorithm is a new type of en- lightened algorithm simulating evolution. This paper puts forward a path planning solution method based on Voronoi diagram algorithm, which enhances the efficiency of unmanned aerial vehicle （UAV） path planning in the case of multiple threat sources distribution. Firstly,this paper gener- ates the weighted Voronoi diagram according to the data information of known threat sources,and defines that the total cost of each edge could be calculated according to the distance between the two points of the edge, then uses the ant colony algorithm combining with the flightable flight point set to carry out the path planning for the UAV in the multiple threat source distribution flight environment. The simulation results verify the feasibility and effectiveness of the proposed method in solving the UAV path planning problem under various combat field environments.