基于ADAMS的工业机器人轨迹精度模型研究

›› 2016, Vol. 29 ›› Issue (4): 20-.

基于ADAMS的工业机器人轨迹精度模型研究

费家人,朱坚民,黄春燕

(上海理工大学机械工程学院,上海 200093)

出版日期:2016-04-15 发布日期:2016-04-26
作者简介:费家人(1990—),女,硕士研究生。研究方向:精密测试。朱坚民(1968—),男,博士,教授。研究方向:机电系统的智能测控。黄春燕(1990—),女,硕士研究生。研究方向:精密测试。
基金资助:
国家自然科学基金资助项目(50975179)

Study on the Model of Trajectory Precision for Industrial Robot Based on ADAMS

FEI Jiaren,ZHU Jianmin,HUANG Chunyan

(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

Online:2016-04-15 Published:2016-04-26

摘要/Abstract

摘要：

预测工业机器人轨迹精度对高精度加工具有重要影响,分析影响其轨迹精度的因素,基于ADAMS提出一种考虑结构参数误差及关节转角偏差的轨迹精度模型。应用激光跟踪仪辨识工业机器人结构参数与名义值间存在的偏差,分析关节转角偏差随工况的变化,在ADAMS环境下建立轨迹精度模型。以UR5机器人为实验对象,API激光跟踪仪为测量仪器对其轨迹精度进行测量,与模型输出结果进行对比,实验结果表明,该模型可准确预测工业机器人轨迹精度,预测精度可达0.5 mm,且参考该预测结果进行误差补偿后,轨迹精度基本达到1 mm以内。

关键词: 工业机器人, 结构参数误差, 关节转角偏差, 误差预测模型

Abstract:

The purpose of this paper is to explore a prediction model of trajectory precision based on ADAMS,which can improve the high precision processing using industrial robots.The main factors influencing trajectory precision are the structural parameters of industrial robots and nominal value and the joint angle deviation.A structural parameters identification scheme is proposed and verified by a laser tracker and analyze the relationship of the joint angle deviation and the change of working condition.A prediction model of trajectory precision in ADAMS is built.Finally,an experiment system is established to verify the prediction model with the API III laser tracker aimed at UR5 as the measuring device.The experiment results show that the prediction model is valid with the precision of prediction close to 0.5 mm,and the trajectory precision is less than 1mm with error compensation.

Key words: industrial robots;error of structural parameters;joint angle deviation;error prediction model

中图分类号:

TP242.2

费家人,朱坚民,黄春燕. 基于ADAMS的工业机器人轨迹精度模型研究[J]. , 2016, 29(4): 20-.

FEI Jiaren,ZHU Jianmin,HUANG Chunyan. Study on the Model of Trajectory Precision for Industrial Robot Based on ADAMS[J]. , 2016, 29(4): 20-.