首页|基于改进哈里斯鹰算法的无人飞行器路径规划

基于改进哈里斯鹰算法的无人飞行器路径规划

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  • 国家科技期刊平台
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针对无人飞行器三维路径规划问题,提出一种基于哈里斯鹰优化(Harris hawks optimization,HHO)算法的无人飞行器三维路径规划算法.首先根据路径规划代价指标和无人飞行器自身性能,建立路径规划模型确立代价函数和约束条件.接着针对传统HHO算法的不足,引入非线性能量因子来平衡全局搜索和局部搜索的关系,使算法避免陷入局部最小值;引入混沌映射对HHO算法进行初始化种群并对其进行局部混沌搜索,增强算法种群多样性和搜索能力.最后通过仿真实验证明,改进的哈里斯鹰优化(improvement Harris hawks optimization,IHHO)算法可以有效规划出安全的无人飞行器航线,并且能够跳出局部最小值和具备较优的收敛速度.
Unmanned aerial vehicles path planning based on improved Harris hawks optimization algorithm
Aiming at the 3D path-planning problem of unmanned aerial vehicles,this paper proposes a 3D path-planning algorithm for unmanned aerial vehicles based on the improved Harris hawks optimization(HHO).First,according to the path-planning cost index and the performance of the unmanned aerial vehicle itself,the path-planning model is built to establish the cost function and constraints.Then,aiming at the shortcomings of the traditional Harris hawks optimization,a nonlinear energy factor is introduced to balance the relationship between global search and local search,lest the algorithm fall into a local minimum;The chaos mapping is introduced to initialize the population of the Harris hawks optimization and perform local chaotic search on it,so as to enhance the population diversity and search capabilities of the algorithm.Finally,it is proved through simulation experiment that improved Harris hawks optimization can effectively plan a safe unmanned aerial vehicles route.And it can jump out of the local minimum,having a better convergence speed.

unmanned aerial vehiclesHarris hawks optimization algorithmpath planningchaos mapnonlinear energyenvironment modelcost functionconstraints

陈立伟、马泽华、王桐、刘松铭

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哈尔滨工程大学信息与通信工程学院,黑龙江哈尔滨 150001

哈尔滨工程大学先进船舶通信与信息技术工业和信息化部重点实验室,黑龙江哈尔滨 150001

无人飞行器 哈里斯鹰优化算法 路径规划 混沌映射 非线性能量 环境模型 代价函数 约束条件

中央高校基本科研业务费专项先进信息技术产业和信息技术部重点实验室项目

KY10800220073AMCIT2101-08

2024

10.11991/yykj.202304038

应用科技
哈尔滨工程大学

应用科技

CSTPCD
影响因子：0.693
ISSN：1009-671X
年,卷(期)：2024.51(2)
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