针对补强片自动贴片系统的手眼标定问题, 为了消除相机安装的垂直度偏差带来的误差, 提出了一种新的手眼标定方法。使用标定板得到相机的外参数, 将外参数与常规的二维标定模型相结合, 从而间接计算出相机坐标系与机器人基础坐标系的齐次坐标转换矩阵, 使手眼标定模型扩展为三维。三维模型的标定计算误差小于0.1 μm, 相比二维模型降低了1个数量级, 有效提高了标定计算精度。利用厚度较小的菲林修正齐次坐标变换矩阵的Z方向分量, 系统具有较高的定位精度, 手眼标定的误差绝对值小于0.015 mm, 有效减小了误差均值, 设备性能得到大幅提高。该方法在系统可控自由度有限的情况下, 能够得到手眼标定问题的唯一解, 提出的三维模型中包括了相机的完整姿态信息, 相比常规的标定方法没有相机安装等额外的限制条件, 能有效提高系统的手眼标定精度。

To eliminate the error of hand-eye calibration caused by installation error associated with the verticality of the camera's optic axis in the automatic stiffness bonder, we proposed a novel method to calculate the homogeneous coordinate transformation between the camera frame and the robot base frame. The external parameters of camera obtained with the calibration boards, were combined with the conventional 2D calibration model, thereby extending the dimensions of the model to 3 and effectively improving the calculation accuracy. The calculation error of the calibration with the 3D model is less than 0.1μm, which decreases by an order of magnitude compared with the 2D model. Using the thin films to modify the value in Z direction in coordinate transformation, the system has high location precision and the error of the calibration is less than 0.015 mm. The mean error is reduced effectively, and the performance of system is significantly improved. The proposed method is capable to obtain the unique solution of calibration equation with the finite degree of freedom system. The 3D calibration model including the whole information associated with the camera pose, has no additional constraints such as camera installation, and can effectively improve the accuracy of hand-eye calibration.