基于改进精英蚁群算法的无人机三维航迹规划  

Three Dimensional Path Planning of UAV Based on Improved Elite Ant Colony Algorithm

作　　者：袁梦顺 陈谋[1] 邵书义[1] 吴庆宪[1] 闫东 YUAN Meng-shun;CHEN Mou;SHAO Shu-yi;WU Qing-xian;YAN Dong(College of Automation,Nanjing University of Aeronautics and Astronautics,Nanjing 211106,China)

机构地区：[1]南京航空航天大学自动化学院,南京211106

出　　处：《火力与指挥控制》2022年第2期37-42,共6页Fire Control & Command Control

基　　金：国家自然科学基金应急管理项目(61751219);航空科学基金(201957052001);装备预研中国电科联合基金(6141B08231110a);“十三五”装备预研基金资助项目(61425040104)。

摘　　要：针对三维地图中的无人机航迹规划问题,提出了一种基于改进精英蚁群算法的航迹规划算法。将算法中的状态转移策略与人工势场法进行融合设计,为障碍物和目标点分别设置斥力场和引力场,指导航迹搜索方向。添加约束条件限制,使航迹能实际可飞。随后当信息素更新时,设置双精英蚂蚁策略和混沌扰动,提高算法的全局搜索能力。引入视线算法减少航迹节点数,平滑航迹。仿真结果表明,搜索所得的无人机航迹均符合需求。For unmanned aerial vehicle(UAV)path planning in three-dimensional map,an improved elite ant colony algorithm is proposed.Firstly,the state transfer strategy in the elite ant colony algorithm is designed to be integrated with the artificial potential field method.Repulsion field for obstacles and gravitational field for target points are set respectively to guide the path search direction.Secondly,the UAV constraint limits are added to make the path actually flyable.Then,when the pheromone is updated,the double elite ant strategy and chaos disturbance are set to improve the global search ability of the algorithm.In addition,line of sight algorithm is introduced to reduce the number of path nodes and to smooth the path.The simulation results show that the UAVpaths obtained from the search all meet the requirements.

关 键 词：无人机 航迹规划 精英蚁群算法 人工势场法 视线算法 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]