基于改进鲸鱼优化算法的轮式移动机器人路径规划  

Wheel Mobile Robot Path Planning Based on Improved Whale Optimization Algorithm

作　　者：吴峥 傅晓锦[1] 李莎[1] 庄瑜 WU Zheng;FU Xiaojin;LI Sha;ZHUANG Yu(Shanghai Dianji University,Shanghai 201306,China)

机构地区：[1]上海电机学院,上海201306

出　　处：《机械设计与研究》2024年第5期167-175,共9页Machine Design And Research

摘　　要：轮式移动机器人路径规划算法存在精度低、稳定性低、迭代周期长、容易陷入局部最优解。针对以上问题,提出了一种基于改进鲸鱼优化算法的轮式移动机器人路径规划技术。首先引入Logistic混沌映射,增加初始解分布的均匀性,降低陷入局部最优解的概率。其次融合共生生物搜索算法优化全局搜索性能,提高算法的收敛速度和鲁棒性。最后,利用高斯变异策略扩展搜索的多样性、提高全局搜索能力、加快收敛速度、增强算法的鲁棒性。研究结果表明:与传统鲸鱼优化算法相比,改进后的算法在路径长度、收敛速度、拐点数和鲁棒性方面具有明显优势,为轮式移动机器人路径规划提供了一种新的方法。The path planning algorithm for wheeled mobile robots faces issues including low accuracy,low stability,long iterative cycles and a tendency to converge to suboptimal solutions.To address these problems,this paper proposes a path planning technique for wheeled mobile robots based on an enhanced whale optimization algorithm.Initially,the logistic chaotic map is introduced to increase the uniformity of the distribution of initial solutions and reduce the probability of converging to local optima.Subsequently,a symbiotic organisms search algorithm is integrated to optimize global search performance,thus enhancing the convergence speed and robustness of the algorithm.Finally,utilizing a Gaussian mutation strategy to expand the diversity of the search,global search capabilities is enhanced,convergence speed is accelerated,and the robustness of the algorithm is strengthened.The research results indicate that compared to the traditional whale optimization algorithm,the improved algorithm exhibits significant advantages in terms of path length,convergence speed,number of turning points,and robustness.This provides a new method for the path planning of wheeled mobile robots.

关 键 词：路径规划 鲸鱼优化算法 LOGISTIC混沌映射 共生生物搜索算法 高斯变异 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]