【摘要】 为了提高工业机器人的绝对定位精度和标定效率，提出一种基于预标定基坐标系及改进迭代扩展卡尔曼滤波(MIEKF)算法的运动学标定方法。该方法的优点在于用采集的位置数据进行基坐标系和工具坐标系预标定，节省两者拟合的时间。在建立位置误差模型时利用相关系数和复共线性分析去除模型的冗余参数。用MIEKF算法辨识模型的几何参数误差。通过实验对比验证，机器人经补偿后的绝对定位精度提高了88.07%。更多还原

【Abstract】 In order to improve the absolute positioning accuracy and calibration efficiency of industrial robots, a kinematic calibration method based on pre-calibrated base coordinate system and modified iterative extended Kalman filter(MIEKF) algorithm was proposed.The advantages of this method were that the collected position data were used for pre-calibration of the base and tool coordinate systems to save the time for fitting both.The correlation coefficient and the multicollinearity analysis were used to remove the redundant parameters of the model when building the position error model, and the MIEKF algorithm was used to identify the geometric parameter errors of the model.The absolute positioning accuracy of the robot after compensation is improved by 88.07% as verified by experimental comparison.更多还原