合模机器人设计及无标定视觉伺服控制方法研究  

Design of Mold-clamping Robot and Research of Uncalibrated Vision Servo Control Method

作　　者：李宗刚[1,2] 王国平 袁博民 杜亚江[1,2] LI Zonggang;WANG Guoping;YUAN Bomin;DU Yajiang(School of Mechanical Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Robot Research Institute,Lanzhou Jiaotong University,Lanzhou 730070,China;Robot Project Department,Gansu Changfeng Electronic Technology Limited Liability Company,Lanzhou 730070,China)

机构地区：[1]兰州交通大学机电工程学院,兰州730070 [2]兰州交通大学机器人研究所,兰州730070 [3]甘肃长风电子科技有限责任公司机器人项目部,兰州730070

出　　处：《兰州交通大学学报》2024年第5期19-28,39,共11页Journal of Lanzhou Jiaotong University

基　　金：国家自然科学基金(61663020);甘肃省高等学校科研项目成果转化项目(2018D-10)。

摘　　要：针对当前铆接过程中合模工艺主要依赖人工完成而导致的工作效率低下问题,设计了一种合模机器人末端执行器,以提高自动化程度和作业效率。为解决工件超出相机视域的问题,提出了一种基于改进图像矩的无标定视觉伺服控制器。在合模过程中,采用递推最小二乘法(RLS)在线估计图像雅可比矩阵,并结合扩展Kalman滤波器,实时输出机械臂关节变化量,以对RLS估计模块进行反馈。仿真结果表明,该控制方法在图像位于相机视域内以及超出相机视域时均能有效提取图像特征。与仅使用RLS方法相比,基于图像矩的控制方法在特征提取效率和抗噪声能力上表现出更优越的性能,且图像矩特征误差的收敛速度更快。实体实验进一步验证了该方法在工件超出相机视域情况下的准确性,成功解决了传统方法的局限性,使合模机器人能够精确定位工件并到达目标位置,从而显著提升铆接过程的自动化水平和工作效率。To address the issue of low work efficiency caused by the reliance on manual processes in the mold clamping phase of riveting,this paper presents a design of an end effector for a clamping robot to enhance automation and operational efficiency.To overcome the challenge of workpieces extending beyond the camera's field of view,an uncalibrated vision servo controller based on improved image moments is proposed.During the clamping process,the recursive least squares(RLS)method is employed to estimate the image Jacobian matrix online,while incorporating an extended Kalman filter to provide real-time feedback on the joint movement of the robotic arm to the RLS estimation module.Simulation results demonstrate that this control method effectively extracts image features both within and beyond the camera's view.Compared to the sole use of the RLS method,the image moment-based control approach exhibits superior performance in feature extraction efficiency and noise resistance,with a faster convergence rate for the image moment feature error.Physical experiments further validate the accuracy of the method when workpieces are outside the camera's field of view,successfully addressing the limitations of traditional methods.This advancement enables the clamping robot to accurately locate workpieces and reach target positions,thereby significantly improving the automation level and work efficiency of the riveting process.

关 键 词：工业机器人 无标定视觉伺服 图像矩 扩展KALMAN滤波器 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]