基于AIXM数据集和改进A^(*)算法的直升机路径规划

Helicopter Path Planning Based on AIXM Dataset and Improved A^(*)Algorithm

针对AIXM数据集(aeronautical information exchange model dataset)在通航应用研究缺乏,以及经典A^(*)算法在直升机路径规划问题中转弯节点多等问题,提出了一种基于AIXM数据集的改进A^(*)算法直升机路径规划方法。首先,分析了AIXM数据集的时空属性,设计了基于时空属性搜索的AIXM障碍物数据查询方法,为进行直升机路径规划奠定了数据环境基础;然后结合直升机性能限制构建了碰撞判断包围盒,基于碰撞包围盒改进经典A^(*)算法,利用AIXM数据障碍物数据与航线数据,提出了一种直升机路径规划方法;通过python与Luaid AIXM 5 Viewer对该方法进行了仿真实验表明,所提方法规划的直升机路径转弯节点少,降低了直升机转弯的频率,规划路径短且符合路径与障碍物之间的安全距离要求。本文研究是将AIXM数据集利用于通航航空情报服务的创新尝试。

The aim of this study is to address the lack of research on the application of AIXM dataset(aeronautical information exchange model dataset)in general aviation,as well as the issue of excessive turning nodes in helicopter path planning when using the classical A^(*)algorithm.An improved A^(*)algorithm helicopter path planning method based on AIXM dataset was proposed.Firstly,the space-time attribute of the AIXM dataset was analyzed,and a query method for AIXM obstacle data based on space-time attribute search was designed,thereby establishing the foundational data environment for helicopter path planning.Then the collision judgment bounding box was constructed according to the performance constraints of the helicopter.Based on this collision bounding box,an improved classical A^(*)algorithm was utilized to propose a method for helicopter path planning using AIXM data of obstacle and route.The simulation experiments conducted using Python and Luaid AIXM 5 Viewer demonstrate that the proposed method for helicopter path planning exhibits a reduced number of turning nodes,decreased frequency of helicopter turns,and ensures a shorter planned path while maintaining the necessary safety distance from obstacles.The method simultaneously represents an efficient endeavor to utilize the AIXM dataset in general aviation scenarios.