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基于CPA方法的串联工业机器人运动学标定精度试验研究 被引量:3

Experimental Study on Accuracy of Kinematic Calibration for Serial Industrial Robots Based on CPA Method
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摘要 几何参数误差是影响工业机器人定位精度的主要误差源,约占总误差的80%以上。基于圆点分析法(circle points analysis,CPA)所标定的几何参数与机器人的实际结构相关,并且能够将几何参数误差与其他误差源解耦。研究表明CPA方法的测量策略对其标定精度具有较大影响。针对基于CPA方法的串联工业机器人运动学标定技术的测量策略展开试验研究,分别对各轴测量角度范围、各轴测量步长、初始位姿构型、靶球安装位置等因素进行了分析,并得出一个优化的测量策略。实验结果表明该测量策略能够有效地提升CPA方法的标定精度,误差减少了43.99%,明显优于其他测量方案。通过与误差模型方法对比,经CPA方法标定的机器人具有更好的全局定位精度。 Geometric parameter errors are the main error source that affects the positioning accuracy of industrial robots.It accounts for more than 80%of the total error.The geometric parameters calibrated based on the circular point analysis method(CPA)are related to the actual structural of robots.It also can decouple geometric parameters errors from the other error sources.Some researches show that the measurement strategy of the CPA method has a great impact on its calibration accuracy.An experimental study was carried out on the measurement strategy of kinematic calibration technology for serial industrial robots based on CPA method.The influences of the measurement angle range of each axis,the measurement step length of each axis,the initial posture configuration,and the target ball installation position on calibration accuracy were analyzed.The optimized measurement strategy of the CPA method was obtained.Experimental results show that the measurement strategy can effectively improve the accuracy of the CPA method.The error is reduced by 43.99%,which is significantly better than other schemes.Compared with the error model method,the robot calibrated by the CPA method has better global positioning accuracy.
作者 孙大林 乔贵方 宋光明 温秀兰 宋爱国 SUN Da-lin;QIAO Gui-fang;SONG Guang-ming;WEN Xiu-lan;SONG Ai-guo(School of Instrument Science and Engineering,Southeast University,Nanjing 210096,China;School of Automation,Nanjing Institute of Technology,Nanjing 211167,China)
出处 《仪表技术与传感器》 CSCD 北大核心 2021年第1期77-83,共7页 Instrument Technique and Sensor
基金 国家自然科学基金(51905258) 江苏省自然科学基金(BK20170763) 江苏省高校自然科学研究面上项目(16KJB460013) 中国博士后科学基金资助(2019M650095)。
关键词 机器人标定 激光跟踪仪 圆点分析法 几何参数标定 运动学标定 robot calibration laser tracker circle point analysis geometric parameter calibration kinematic calibration
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