摘要
传统方法求解复杂环境下无人机航迹规划问题容易出现全局搜索能力差,易收敛在局部最优解。针对这一问题,提出一种多策略改进的自适应蜜獾优化算法(IHBA)。建立了无人机的飞行环境模型,并围绕航迹长度、飞行高度和飞行转角等因素构造适应度函数,同时将三维航迹规划问题转换为多约束目标优化问题。为了提升蜜獾优化算法对目标问题的搜索精度和效率,设计Tent混沌与对立学习种群初始化提升初始航迹的多样性,利用非线性动态自适应密度因子实现全局最优航迹的探采均衡,引入自适应挖掘策略提高算法的开采精度,同时结合柯西算子的自适应透镜成像变异算子丰富搜索空间,避免局部最优。利用IHBA算法求解航迹规划问题,建立2个场景进行仿真验证。实验表明:改进算法搜索的最优航迹不仅安全避障,且航迹开销更小,搜索效率更高。
The traditional methods for solving UAV track planning problems in complex environments tend to have poor global search ability and tend to converge to local optimal solutions.To solve this problem,a multi-strategy improved adaptive honey badger optimization algorithm IHBA was proposed in this paper.The flight environment model of UAVs was established,and the fitness function was constructed around the factors of track length,flight altitude and flight angle.And the three-dimension track planning problem was transformed into a multi-constrained optimization problem.In order to improve the search accuracy and efficiency of the honey badger optimization algorithm on the target problem,a Tent chaos and opposition-learning population initialization strategy was designed to improve the diversity of the initial track.A nonlinear dynamic adaptive density factor was used to achieve the exploration and mining balance of the global optimal track.An adaptive mining strategy was introduced to improve the mining accuracy of our algorithm.At the same time,an adaptive lens imaging mutation operator combined with Cauchy operator was designed to enrich the search space and avoid local optimization.The IHBA was used to solve the flight path planning problem,and the simulation was verified in two different scenarios.The experimental results show that the optimal track searched by the improved algorithm is not only safe for avoiding obstacles,but also has less track cost and higher search efficiency.
作者
辛富强
赵召娜
韩娜
殷小曼
冯笑
XIN Fuqiang;ZHAO Zhaona;HAN Na;YIN Xiaoman;FENG Xiao(State Grid Electric Power Space Technology Company Limited;School of Cyberspace Security,Beijing University of Posts and Telecommunications)
出处
《仪表技术与传感器》
北大核心
2025年第7期84-93,126,共11页
Instrument Technique and Sensor
基金
国家自然科学基金项目(62001055)。
关键词
无人机
航迹规划
蜜獾优化算法
透镜成像
柯西分布
unmanned aerial vehicle
flight path planning
honey badger optimization algorithm
lens imaging
Cauchy distribution
