复杂低空环境下无人机三维航迹智能规划  

Intelligent 3D Path Planning of UA V in Complex Low-altitude Environment

作　　者：张赫 张宾 靳崇 赵雁妍 梁晓 ZHANG He;ZHANG Bin;JIN Chong;ZHAO Yanyan;LIANG Xiao(North Automatic Control Technology Institute,Taiyuan 030006,China;The Second Military Representative Office of the Army Armament Department in Taiyuan Region,Taiyuan 030006,China)

机构地区：[1]北方自动控制技术研究所,太原030006 [2]陆军装备部驻太原地区第二军代室,太原030006

出　　处：《火力与指挥控制》2025年第1期72-79,共8页Fire Control & Command Control

摘　　要：选取复杂低空环境对无人机的三维航迹规划展开研究,通过航迹规划建模、蚁群算法改进和仿真验证分析等方法获得了一种航迹规划方法。通过融入无人机机动性能约束、规划环境外部约束和航迹综合代价建模等优化方法,重新建立航迹规划目标函数,使其更能真实地描述无人机的实际作战环境。从3个方面对基本蚁群算法进行了改进,包括非均匀初始化信息素合理设置、增加启发因子改进状态转移概率和优化改进信息素更新机制。通过仿真实验表明,改进后的蚁群算法所获取的最优航迹,能够有效地规避地形地貌、禁飞区和空域可用空间的限制影响,切实减少了迭代次数,在较大程度上提升了航迹规划的质量,具备一定的实用价值。Aiming at the three-dimensional path planning problem of UAV in complex low-altitude environment,a path planning method is proposed based on the path planning modeling,ant colony algorithm improvement and simulation,validation analysis and other methods,considering terrain influence and threat information.The objective function of path planning is reconstructed by integrating maneuverability performance constraints of UAV,external constraints of planning environment,comprehensive cost modeling of path and other optimization methods,the UAV actual combat environment is described more realistically.The basic ant colony algorithm is improved from three aspects,such as reasonable setting for non-uniform initialization of pheromones,increasing heuristic factors to improve state transition probability,and improving pheromone updating mechanism.The simulation experiment shows that the optimal path obtained by improved ant colony algorithm can effectively avoid the effects of topography,no-fly zones and airspace available space restrictions,the number of iterations is reduced and the quality of flight path planning is greatly improved,it has certain practical value.

关 键 词：无人机 三维航迹规划 威胁规避 改进蚁群算法 

分 类 号：TH17[机械工程—机械制造及自动化]