基于A星算法的无人机路径规划优化模型研究

在分析传统无人机路径规划方法应用局限的基础上,针对传统A星算法启发函数单一、拐点冗余,以及效率不够高等系列问题,以虚拟城市地理环境为研究背景,通过提出面向起讫节点方位角的A星算法加速优化、启发式搜索中动态加权重构评价函数的A星算法加速优化和顾及Floyd算法插点策略的A星算法路径优化等层次递进的算法优化策略,解决了对A星算法搜索方向的量化约束、搜索权重数值的优化重构及冗余拐点的插点删除等技术问题,实现了改进后的A星算法运行效率的显著提高及最短路径判定准确性的明显提升。

Research on UAV path planning optimization model based on A-star algorithm

Based on the analysis of the application limitations of traditional UAV path planning method,aiming at a series of problems,such as the heuristic function is single,the inflection points are redundant and efficiency is not high enough,based on the research background of virtual city geographic environment,a hierarchical algorithm optimization strategy is proposed,which is the A-star-algorithm accelerated optimization oriented to the azimuth angle of star and end nodes,the A-star-algorithm accelerated optimization of dynamic weighted reconstruction evaluation function on heristic search,and the A-star-algorithm path optimization considering the Floyd-algorithm insertion strategy.Finally,the problems of the quantitative constraints of search direction,optimization reconstruction of search weight and inertion point deletion of redundant inflection points are solved.The experimental result shows that the efficiency of the improved A-star algorithm and the accuracy of the shortest path decision are improved significantly.