增强型霜冰优化算法的复杂环境下机器人路径规划  

Enhanced rime optimization algorithm for robot path planningin complex environments

作　　者：谢灿坤 于丽娅[2] 张涛[3] 任文杰 莫代贵 Xie Cankun;Yu Liya;Zhang Tao;Ren Wenjie;Mo Daigui(State Key Laboratory of Public Big Data,Guizhou University,Guiyang 550025,China;School of Mechanical Engineering,Guizhou University,Guiyang 550025,China;China Telecom Co.,Ltd.Guizhou Branch,Guiyang 550025,China;Guiyang Aluminum Magnesium Design&Research Institute Co.,Ltd.,Gui-yang 550025,China)

机构地区：[1]贵州大学省部共建公共大数据国家重点实验室,贵阳550025 [2]贵州大学机械工程学院,贵阳550025 [3]中国电信有限公司贵阳分公司,贵阳550025 [4]贵阳铝镁设计研究院有限公司,贵阳550025

出　　处：《计算机应用研究》2025年第1期185-195,共11页Application Research of Computers

基　　金：贵州大学横向项目(GYYZKY2022006JY);贵州省科技计划资助项目(黔科合基础-ZK[2024]一般019)。

摘　　要：针对原始霜冰优化算法(RIME)在移动机器人路径规划问题中存在易陷入局部最优和收敛速度慢等问题,提出一种增强型霜冰优化算法(ERIME)用于对复杂环境下移动机器人进行路径规划。首先,采用基于sine混沌映射的透镜成像种群选择策略对种群初始化阶段进行增强以增加种群多样性,使算法更好地进行探索和开发;其次,使用随机因子控制的最值搜索策略和质心中点引导的开发机制对算法的探索和开发阶段进行改进,增强算法跳出局部最优解的能力,更好地探索全局最优解,并加快算法的收敛速度;此外,建立ERIME算法的Markov链模型,证明了算法的全局收敛性。为验证ERIME的有效性,对该算法采用CEC2017测试集进行验证,并与其他知名的元启发式算法进行比较,结果表明该算法具有良好的性能。最后,将其应用于复杂环境下的移动机器人路径规划问题中,实验结果表明,ERIME可以高效地为机器人进行路径规划,且可以找到一个非常优质的路径。Addressing the problems of the RIME in the mobile robot path planning problem,such as easy to fall into the local optimum and slow convergence speed,this paper proposed an enhanced rime optimization algorithm(ERIME)for the path planning of mobile robots in the complex environment.Firstly,this algorithm designed a lens imaging population selection strategy based on sine chaos mapping to improve the population initialization stage to increase the population diversity,so that the algorithm could be better explored and exploited.Secondly,this algorithm designed a stochastic factor-controlled optimal search strategy and a centroid-guided development mechanism to improve the exploration and exploitation stages of the algorithm,so as to enhance the algorithm’s ability to escape from the local optimal solutions,better explore the global optimal solution,and accelerate the convergence speed of the algorithm.Additionally,this paper proposed a Markov chain model of the ERIME algorithm and proved the global convergence of the algorithm.To verify the effectiveness of ERIME,this paper validated the algorithm using the CEC2017 test set and compared it with other well-known meta-heuristic algorithms.The results show that the algorithm performs well.Finally,this paper applied the ERIME algorithm to the path planning problem of mobile robots in complex environments.The experimental results demonstrate that the proposed algorithm efficiently plans the robot’s path and finds a high-quality route.

关 键 词：机器人 路径规划 霜冰优化算法 栅格地图 sine映射 最值搜索 

分 类 号：TP249[自动化与计算机技术—检测技术与自动化装置]