基于改进人工鱼群算法的无人机集群航迹规划  

UAVs Path Planning Based on Improved Artificial Fish Swarm Algorithm

作　　者：林志坚 杨柳庆[1,2] 屠壮 张勇 LIN Zhijian;YANG Liuqing;TU Zhuang;ZHANG Yong(College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016;Unmanned Aerials Vehicles Research Institute,Nanjing University of Aeronautics and Astronautics,Nanjing 210016;Key Laboratory of Unmanned Aerial Vehicle Technology,Ministry of Industry and Information Technology,Nanjing 210016)

机构地区：[1]南京航空航天大学自动化学院,南京210016 [2]南京航空航天大学无人机研究院,南京210016 [3]中小型无人机先进技术工业和信息化部重点实验室,南京210016

出　　处：《舰船电子工程》2024年第12期33-38,共6页Ship Electronic Engineering

基　　金：国家自然科学基金项目(编号:52272369)资助。

摘　　要：针对无人机集群在复杂战场环境下的高效快速航迹规划,提出一种融合自适应机制的改进人工鱼群算法。在传统的人工鱼群算法的基础上引入基于Logistic映射的种群初始化,增强种群的多样性。并提出一种自适应视野模型,可根据寻优情况自适应调整鱼群视野大小,提高了算法的收敛速度。最后于人工鱼群行为加入基于莱维飞行轨迹的随机游走,增强算法的全局优化能力和收敛精度。将该改进算法与传统的人工鱼群算法,粒子群算法进行对比,仿真结果表明改进的人工鱼群算法规划出的航路代价最小,且算法的收敛精度与收敛速度得到极大提升。Aiming at the efficient and fast path planning of UAVs in complex battlefield environment,an improved artificial fish swarm algorithm with adaptive mechanism is proposed.On the basis of traditional artificial fish swarm algorithms,the popula⁃tion initialization based on Logistic mapping is introduced to enhance the diversity of the population.An adaptive visual field model is presented,which can adjust the visual field size of fish swarm adaptively according to the optimization situation,so it can improve the convergence speed of the algorithm.Finally,the random walk based on Lévy flight path is added to the artificial fish behavior to enhance the global optimization ability and convergence accuracy of the algorithm.Comparing the improved algorithm with tradition⁃al artificial fish swarm algorithm and particle swarm optimization,the simulation results show that the improved algorithm has the smallest path cost,meanwhile the convergence accuracy and speed of the algorithm have been greatly improved.

关 键 词：人工鱼群算法 航迹规划 自适应视野 莱维飞行 

分 类 号：V249.2[航空宇航科学与技术—飞行器设计]