一种用于Mecanum底盘的自适应路径规划算法  

An Adaptive Path Planning Algorithm for Mecanum Wheels Chassis

作　　者：黄晓宇 孙勇智[1,2] 李津蓉 刘薇[1,2] 李恒通 HUANG Xiaoyu;SUN Yongzhi;LI Jinrong;LIU Wei;LI Hengtong(School of Automation and Electrical Engineering,Zhejiang University of Science and Technology,Hangzhou 310023,China;Key Institute of Robotics Industry of Zhejiang Province,Hangzhou 310023,China)

机构地区：[1]浙江科技学院自动化与电气工程学院,杭州310023 [2]浙江省机器人产业学院,杭州310023

出　　处：《机械科学与技术》2025年第3期530-537,共8页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目(62173306);教育部产学合作协同育人项目(201901014014)。

摘　　要：为解决狭小且复杂工作环境下,麦克纳姆轮自动导引车(Automated guided vehicle,AGV)最优路径规划问题,提出了一种基于麦克纳姆轮底盘运动学模型改进的A^(*)算法。首先,将麦克纳姆轮AGV等效为二维最小外接矩形,利用其全向移动特性设计路径搜索策略;其次为提高规划路径的安全性,依据模型特征构建了拓展模型避障矩阵;最后引入二维高斯核函数自适应调整算法实际代价函数和启发估计代价函数的权重系数,平衡搜索的全局性和快速性。仿真试验结果表明:改进的算法在搜索时间和安全性能均高于普通算法,提高了麦克纳姆轮AGV通过狭窄空间或转弯死角的能力,增强了路径搜索效率。In order to solve the problem of optimal path planning of Mecanum wheels automated guided vehicle(AGV)in a narrow and complex working environment,an improved A^(*)algorithm based on the kinematic model of Mecanum wheels chassis was proposed.Firstly,the Mecanum wheels AGV was equivalent to a two-dimensional minimum bounding rectangle,and its omnidirectional movement characteristics were used to design the path search strategy.Secondly,in order to improve the safety of the planned path,an extended model obstacle avoidance matrix was constructed according to the characteristics of the model.Finally,two-dimensional Gaussian kernel function was introduced to adaptively adjust the weight coefficients of the actual cost function and heuristic estimation cost function of the algorithm,so as to balance the global and fast search.The simulation results demonstrate that the improved algorithm is better than the common algorithm in search time and safety performance,and improves the ability of Mecanum wheels AGV to pass through narrow space or turn dead corner,and enhances the path search efficiency.

关 键 词：麦克纳姆轮 A^(*)算法 外接矩形 拓展模型避障矩阵 二维高斯核函数 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP242[自动化与计算机技术—控制科学与工程]