摘要
针对山地环境下物流无人机航迹规划问题,提出一种基于改进美洲狮算法(SWPO)的无人机三维航迹规划方法。首先,构建含有威胁区域的三维环境模型;其次,为了改善初始种群的多样性,采用Sinusoidal混沌序列进行种群初始化;然后,为了增强算法的全局搜索能力,在美洲狮算法的探索阶段引入回波扰动更新策略,增强算法跳出局部最优解的能力;在开发阶段,引入拥挤调控机制,进一步提升算法的寻优效率;最后,通过真实DEM数据地图的仿真实验。实验结果表明:SWPO算法在求解物流无人机三维航迹规划问题时寻优效率更高。
Aiming at the logistics UAV path planning problem under the mountainous environment,this paper proposes a three-dimensional path planning method for logistics UAV on the improved puma algorithm(SWPO).First,the three-dimensional environment model containing threat areas is constructed.Second,in order to improve the diversity of the initial,the sinusoidal chaotic sequence is used to initialize the population.Then,in order to enhance the global search ability of the algorithm,the echo disturbance update strategy is introduced in the stage of the puma algorithm to enhance the ability of the algorithm to jump out of the local optimal solution.In the development stage,the congestion regulation mechanism is introduced to further improve optimization efficiency of the algorithm.Finally,the simulation experiment is carried out through the real DEM data map.The experimental results show that the SWPO algorithm has higher optimization efficiency when the three-dimensional path planning problem of logistics UAV.
作者
郭锦辉
贾通
韩阳
GUO Jinhui;JIA Tong;HAN Yang(School of Electronic Information,Xi'an Polytechnic University,Xi'an 710048,China)
出处
《物流科技》
2026年第3期61-66,共6页
Logistics Sci Tech
基金
国家自然科学基金项目(51905405)。
关键词
物流配送
无人机
航迹规划
美洲狮算法
logistics and distribution
UAV
track planning
puma algorithm
