改进哈里斯鹰算法的仓储机器人路径规划研究  

Research on Path Planning of Warehouse Robot with Improved Harris Hawks Algorithm

作　　者：雷旭[1] 陈静夷 陈潇阳 Lei Xu;Chen Jingyi;Chen Xiaoyang(School of Electronic and Control Engineering,Chang'an University,Xi'an 710064,China)

机构地区：[1]长安大学电子与控制工程学院,陕西西安710064

出　　处：《系统仿真学报》2024年第5期1081-1092,共12页Journal of System Simulation

基　　金：贵州省科技计划(211432200042)。

摘　　要：为提高静态环境下仓储移动机器人路径规划效率,解决传统哈里斯鹰(Harris Hawks optimization, HHO)算法在路径规划中存在收敛速度慢且易陷入局部最优的问题,提出了一种基于Tent混沌映射融合柯西反学习变异的哈里斯鹰优化算法(HHO algorithmbasedon Tentchaotic mapping hybrid Cauchy mutation and inverse learning, TCLHHO)。通过Tent混沌映射增加种群多样性,以提高算法的收敛速度;提出指数型的猎物逃逸能量更新策略,以平衡算法的全局搜索和局部开发能力;通过柯西反学习变异策略对最优个体进行扰动,扩大算法的搜索范围,增强全局搜索能力。根据真实仓储环境搭建二维栅格环境模型,并在Matlab中进行仿真对比实验。结果表明:该算法的规划速度、最优路径长度以及最优路径转折次数较对比算法具有较好的效果,验证了应用于智能仓储环境下改进的HHO路径规划问题的可行性和鲁棒性。To improve the path planning efficiency of warehouse mobile robots in static environments,and to solve the problems of slow convergence and local optimum of traditional Harris Hawk(HHO)algorithm in path planning,a Harris Hawk optimization algorithm based on Tent chaotic mapping fused with Cauchy's back-learning variant(TCLHHO)is proposed.The population diversity is increased by Tent Chaotic mapping to speed up convergence.An exponential prey escape energy updating strategy is proposed to balance the global search and local exploitation capabilities of the algorithm.The optimal individual is disturbed by Cauchy mutation operator and inverse learning strategy to expand the search range and enhance the global optimization capability.A two-dimensional grid mapping model is built according to the warehousing environment,and a comparison simulation experiment is carried out with Matlab.The results showed that the proposed algorithm had a better performance in planning speed,path length and number of turning points compared with other algorithms,which verifies the feasibility and robustness of the improved HHO algorithm for path planning in the intelligent storage environment.

关 键 词：移动机器人 路径规划 哈里斯鹰优化算法 栅格地图 多策略改进 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TP242[自动化与计算机技术—计算机科学与技术]