复杂环境下无人机路径规划及其改进型人工兔优化  

UAV Path Planning in Complex Environments and Its Improved Artificial Rabbits Optimization Algorithm

作　　者：尹安琳 张著洪 Yin Anlin;Zhang Zhuhong(Guizhou Provincial Characteristic Key Laboratory of System Optimization and Scientific Computation,College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学大数据与信息工程学院贵州省系统优化与科学计算特色重点实验室,贵州贵阳550025

出　　处：《系统仿真学报》2025年第1期79-94,共16页Journal of System Simulation

基　　金：国家自然科学基金(62063002)。

摘　　要：针对复杂障碍物环境下无人机安全、高效飞行的路径规划问题,探讨其优化模型的设计与求解算法。模型设计中,以距离、角度、高度及飞行威胁代价为性能指标,以地域、空域障碍物为约束,建立基于权重系数法与柱坐标系的单性能指标路径规划模型;针对人工兔优化算法存在初始种群分布不均匀、勘探能力和开采能力不平衡,以及局部搜索能力不足的问题,利用SPM混沌映射改善初始种群分布;借助精英个体引导策略增强局部搜索能力;利用改进型能量收缩策略平衡全局与局部搜索能力,提出一种计算复杂度由种群规模确定且能求解大规模优化问题的改进型人工兔优化算法。实验表明,已获路径规划模型的路径规划方案能在一定程度上缓解航迹点数的增加对求解性能的影响,同时优化算法处理大规模优化问题及复杂障碍物威胁环境下无人机路径规划问题具有明显优势。The work probes into the model design of reliable and effective UAV path planning in complex obstacle environments and its related optimization algorithm.In the model design,a weight coefficient method and cylindrical coordinate system-based single-objective path planning model is developed to solve the UAV's flight path,in which the distance,angle,height and threat cost are taken as performance indices and obstacles in the ground and spatial regions are regarded as constraints.In the algorithm design,the SPM chaotic mapping is used to improve the initial population distribution of the artificial rabbit optimization algorithm in view of the problems of uneven distribution of the initial population,the imbalance between exploration and exploitation capacities and the insufficient local search capacity.The local search ability is enhanced by the elite individual guidance strategy.An improved artificial rabbits optimization algorithm with computational complexity determined by population size is proposed to solve large-scale optimization problems.The comparative experiments have validated that,the path planning model is available and can alleviate the influence of the increasing number of track points to the quality of the path planning scheme,and at the same time the improved algorithm can effectively handle high-dimensional optimization problems and is of potential value for the UAV path planning problem.

关 键 词：无人机路径规划 人工兔优化 柱坐标系 大规模优化 精英个体引导策略 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]