基于改进白鹭群优化算法的移动机器人路径规划  

Mobile robot path planning based on improved egret swarmoptimization algorithm

作　　者：赵正君 胡立坤[1] 蔡成杰 韦文扬 ZHAO Zhengjun;HU Likun;CAI Chengjie;WEI Wenyang(School of Electrical Engineering,Guangxi University,Nanning 530004,China)

机构地区：[1]广西大学电气工程学院,南宁530004

出　　处：《现代制造工程》2025年第2期37-43,150,共8页Modern Manufacturing Engineering

基　　金：广西科技计划项目(桂科AB21220039)。

摘　　要：针对改进智能优化算法规划效率低、搜索时间长、路径较为曲折等问题,将白鹭群优化算法首次应用于移动机器人路径规划,并提出了一种基于改进白鹭群优化算法的移动机器人路径规划方法。该算法在探索阶段利用对立学习进行种群初始化,以降低路径搜索代价;采用正余弦算法和贪婪策略对白鹭个体位置更新予以改进,以平衡算法的局部开发和全局搜索能力;利用坐标微调策略以获得安全可靠的规划路径。在优化阶段采用垂距限值法和分段贝塞尔曲线对路径进行优化处理,以得到移动机器人的最终运动路径。仿真结果表明,该算法较对比算法路径规划效率显著提高,总体耗时更短,路径更优,能减少路径转弯次数,进而提升移动机器人的整体工作效率。Addressing issues such as low planning efficiency,long search time,and complex paths in improving intelligent optimization algorithms,the egret swarm optimization algorithm was first applied to mobile robot path planning,and a new method for mobile robot path planning based on the improved egret swarm optimization algorithm was proposed.In the exploration stage,the algorithm utilized adversarial learning for population initialization to reduce the cost of path search;the sine cosine algorithm and greedy strategy were used to improve the updating of individual positions of egrets,in order to balance the local development and global search capabilities of the algorithm;coordinate fine-tuning strategy was used to obtain a safe and reliable planning path.In the optimization stage,the vertical distance limit method and segmented Bessel curve were used to optimize the path,in order to obtain the final motion path of the mobile robot.The simulation results show that this algorithm significantly improves the efficiency of path planning compared to the comparative algorithm,with shorter overall time consumption and better paths.It can reduce the number of path turns and thereby improve the overall work efficiency of mobile robots.

关 键 词：路径规划 路径优化 白鹭群优化算法 坐标微调策略 正余弦算法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]