检索结果-南通市图书馆

Precision measurement and compensation of kinematic errors for industrial robots using artifact and machine learning

引用

Advances in Manufacturing 2022年第3期10卷 397-410页

作者： Ling-Bao Kong Yi Yu Shanghai Engineering Research Center of Ultra-precision Optical Manufacturing Department of Optical Science and EngineeringFudan UniversityShanghai 200438People's Republic of China

Industrial robots are widely used in various areas owing to their greater degrees of freedom(DOFs)and larger operation space compared with traditional frame movement systems involving sliding and rotational stages.However,the geometrical transfer of joint kinematic errors and the relatively weak rigidity of industrial robots compared with frame movement systems decrease their absolute kinematic accuracy,thereby limiting their further application in ultraprecision manufacturing.This imposes a stringent requirement for improving the absolute kinematic accuracy of industrial robots in terms of the position and orientation of the robot arm end.Current measurement and compensation methods for industrial robots either require expensive measuring systems,producing positioning or orientation errors,or offer low measurement accuracy.Herein,a kinematic calibration method for an industrial robot using an artifact with a hybrid spherical and ellipsoid surface is proposed.A system with submicrometric precision for measuring the position and orientation of the robot arm end is developed using laser displacement sensors.Subsequently,a novel kinematic error compensating method involving both a residual learning algorithm and a neural network is proposed to compensate for nonlinear errors.A six-layer recurrent neural network(RNN)is designed to compensate for the kinematic nonlinear errors of a six-DOF industrial robot.The results validate the feasibility of the proposed method for measuring the kinematic errors of industrial robots,and the compensation method based on the RNN improves the accuracy via parameter fitting.Experimental studies show that the measuring system and compensation method can reduce motion errors by more than 30%.The present study provides a feasible and economic approach for measuring and improving the motion accuracy of an industrial robot at the submicrometric measurement level.

关键词： Industrial robot kinematic error Calibration Machine learning Recurrent neural network(RNN)

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：