摘要
为了解决三维复杂环境下的无人机航迹规划问题,提出一种基于改进灰狼优化算法的无人机三维航迹规划方法.模拟真实的地理环境,建立三维地形模型和禁飞区模型,构造合理的评价函数.在改进算法中,设计一种基于贪婪思想和变异策略的初始化方法,提升了初始种群的平均适应度值;将一种非线性递减函数引入距离控制参数,解决了灰狼优化算法开发能力不足的问题;设计一种动态加权平均和静态平均混合的位置更新策略,解决了灰狼优化算法位置更新策略不灵活的问题.仿真结果表明:该算法相比于其他几种相关算法,航迹代价较小、收敛速度较快且效果更稳定.
A three-dimensional route planning method was presented for unmanned aerial vehicle based on improved grey wolf optimizer algorithm in complex three-dimensional environment.A three-dimensional terrain model and a no fly zone model were established for simulate the real geographical environment.A reasonable evaluation function for three-dimensional route planning for unmanned aerial vehicle was constructed.In the improved algorithm,an initialization method based on greedy guidance strategy and mutation strategy was designed,which could improve the average fitness values of the initial population individuals.A nonlinear decreasing function was introduced into the distance control parameter,which could improve the exploration ability of the algorithm.A dynamic weighted average and static average hybrid location update strategy was presented,which could increase flexibility for the algorithm.Simulation results show that compared with a variety of related algorithms,the algorithm has less track cost and faster convergence speed.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2017年第10期38-42,共5页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
国家自然科学基金资助项目(61105083)
关键词
三维航迹规划
灰狼优化
无人机
贪婪思想
混合机制
three-dimensional route planning
grey wolf optimizer
unmanned aerial vehicle
greedyidea
mixed mechanism
