中文摘要：

现有的机器人参数辨识的方法所能提高的绝对定位精度有限,是由于关节和连杆柔度等非几何因素造成误差在空间中分布不均匀.为此,本文提出了一种变参数误差模型.由于各轴之间耦合,为了便于求解,提出采用空间网格来处理该变参数误差模型,同时提出了一套规则的参数辨识采样点选取方法.利用改进型的Levenberg-Marquardt迭代最小二乘法求出各网格对应的参数误差的全局收敛解.最后,利用激光跟踪仪在KUKA工业机器人上进行运动学标定验证补偿效果.验证结果表明：能将机器人的绝对定位精度平均值从0.901 mm提高到0.115 mm.

英文摘要：

Absolute positioning accuracy can only be limitedly improved by the existing robot parameter identification, because the errors are not evenly distributed in the robot working space on account of the compliance of links and joints and other non-geometric factors. In view of these, a variable parameter error model is presented. Due to the coupling between the axis, space grid is presented to deal with the variable parameter error model in order to simplify the solution. Moreover, a kind of regular sampling point selection method is proposed. Futhurmore, the modified Levenberg-Marquardt iterative least-square is applied to the global convergence solution of the parameter error of each space grid. Finally, a kinematic parameter calibration experiment on the KUKA industrial robot is completed with the help of a laser track to demonstrate the effectiveness of the compensation. The result shows that the average absolute positioning accuracy of the robot can be improved from 0.901 mm to 0.115 mm.