基于光学运动跟踪系统的机器人末端位姿测量与误差补偿

doi:10.13973/j.cnki.robot.180176

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戴厚德, 曾现萍, 游鸿修, 苏诗荐, 曾雅丹, 林志榕. 基于光学运动跟踪系统的机器人末端位姿测量与误差补偿[J]. 机器人, 2019, 41(2): 206-215.DOI: 10.13973/j.cnki.robot.180176. DAI Houde, ZENG Xianping, YOU Hongxiu, SU Shijian, ZENG Yadan, LIN Zhirong. Pose Measurement and Error Compensation of the Robot End-Effector Based on an Optical Tracking System. ROBOT, 2019, 41(2): 206-215. DOI: 10.13973/j.cnki.robot.180176.

摘要针对工业机器人绝对定位精度较低的问题，采用加拿大NDI公司的Optotrak Certus HD光学运动跟踪系统作为机器人位姿的测量设备，提出了一种基于再生权最小二乘法的最优剪枝极限学习机算法，通过该算法将机器人目标位姿映射到修正位姿上，实现了对机器人末端位姿补偿的效果.利用爱普生6轴机器人末端进行实验，在不同速度下完成直线轨迹运动、圆轨迹运动以及离散随机运动，对该误差补偿方法的有效性进行验证和分析.结果表明，该误差补偿方法均能提高机器人的位姿精度，其测试点在X、Y、Z三轴总方向上的绝对位置精度为0.06 mm~0.25 mm，比无补偿时的2 mm~3 mm有了1个数量级的提高；而姿态误差补偿后，其均方根误差和平均绝对误差均减小到未补偿时姿态误差的26.09%.同时，该补偿方法还可有效降低异常值的影响，具有良好的稳健性.

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	戴厚德
	曾现萍
	游鸿修
	苏诗荐
	曾雅丹
	林志榕

关键词 ：工业机器人标定, 绝对定位精度, 光学跟踪, 再生权最小二乘法, 最优剪枝极限学习机

Abstract：For the problem of low absolute positioning accuracy in industrial robots, the Optotrak Certus HD optical motion tracking system made by NDI company in Canada is utilized as the measurement device for the robot pose, and an optimallypruned extreme learning machine (OPELM) algorithm based on the self-born weighted least squares (SBWLS) method is proposed. The algorithm realizes the pose compensation effect of the robot end-effector by mapping the robot target pose to the revised pose. In order to verify and analyze the validity of the error compensation method, the end-effector of the Epson's 6-axis robot is used to perform different motion modes, i.e., linear motion, circular motion, and discrete random motion, at a series of speeds in the experiment. The results show that the proposed error compensation method improves the pose accuracy of robot end-effector, and the total absolute positioning accuracy of the test point in X, Y, and Z axes is raised from 2 mm~3 mm to 0.06 mm~0.25 mm, which means the positioning accuracy is increased by an order of magnitude. What's more, the root-mean-square error and mean absolute error after compensation are reduced to 26.09% of the uncompensated errors. Meanwhile, the compensation method also significantly decreases the influence of the outliers, and possesses the outstanding robustness.

Key words： industrial robot calibration absolute positioning accuracy optical tracking self-born weighted least squares method optimally-pruned extreme learning machine

收稿日期: 2018-03-01 录用日期: 2018-07-30

TP241.2

基金资助:国家自然科学基金（61501428）；中国科学院科研装备研制项目（YZ201510）；中国科学院－（台湾）工业技术研究院两院合作计划（CAS-ITRI201504，CAS-ITRI201605，CAS-ITRI201701）；福建省科技计划（2018H01010113）

通讯作者: 曾现萍 E-mail: mrszxp@fjirsm.ac.cn

作者简介: 戴厚德(1982-),男,博士,研究员.研究领域:运动检测与机器人定位导航技术
曾现萍(1990-),女,硕士,助理工程师.研究领域:工业自动化,机器人电磁定位导航技术
游鸿修(1976-),男,博士,特聘研究员.研究领域:机器人性能检测与创新技术.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.180176 或 https://robot.sia.cn/CN/Y2019/V41/I2/206

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