基于引导点的无人机三维航迹规划方法  

The UAV 3D Route Planning Method Based on the Guide Points

作　　者：刘琼昕[1,2] 王景[1,2] 高春晓[1,2] 宋晔[1,2] 高超[1,2] 郝贵青[1,2] 李沛伦[1,2] 朱磊[1,2] 

机构地区：[1]北京理工大学北京市海量语言信息处理与计算应用工程技术研究中心,北京100081 [2]北京理工大学计算机学院,北京100081

出　　处：《北京理工大学学报》2014年第11期1163-1168,共6页Transactions of Beijing Institute of Technology

摘　　要：为提高无人机航迹规划的速度,提出了一种基于引导点的航迹规划方法.该方法结合了不同规划方法的优势,将无人机航迹规划分为两个层次:全局规划和局部规划.全局规划利用遗传算法规划出最优或次优的区域点集,然后产生区域的引导点列;局部规划根据全局规划提供的引导点列,利用SAS(sparse A search)算法快速规划出满足约束条件的可行航迹.仿真实验表明,该方法较好地结合了遗传算法和SAS算法的优势,规划航迹效果优于单一的遗传算法和SAS算法,并且有效地提高了规划速度.Fast track planning capability is one of the requirements of the UAV mission planning system. In order to improve the speed of the UAV route planning, a 3D fast path planning method based on guide points was presented in this paper. A tiered strategy was used that the UAV flight path planning was divided into two levels： global planning and local planning. GA algorithm was used for global planning to generate a regional set of points which were in optimal or suboptimal planning areas, and guide points were generated from these areas. SAS （sparse A search） algorithm was used for local planning according to the guidance provided by the global planning, which will result in a feasible track rapidly. Simulation results show that the method combines the advantages of genetic algorithm and SAS algorithm. The planning track is better than the simplex GA or SAS algorithm, and improves the speed of planning evidently.

关 键 词：航迹规划 引导点 分层策略 稀疏A＊ 遗传算法 

分 类 号：V249[航空宇航科学与技术—飞行器设计]