视觉测量在机器人加工过程手眼标定中的应用

针对高精度测量辅助机器人加工的手眼标定,提出一种基于三维视觉测量的精确手眼标定方法,该方法考虑了非线性优化和初值计算中建模误差的影响。为了提高求解精度,在传感器框架中建立了具有更精确参考点的非线性标定模型,提出一种结合传感器测量和机器人位置随机误差的迭代权重优化解。在初值解中,建立考虑基础参考测量误差的测量平差模型,并使用拉格朗日乘子进行求解。仿真对比结果表明：该方法在估计手眼变换参数方面比其他典型方法具有更高的精度。最后通过搭建实验平台,进一步验证了所提方法在求解精度测试上的优越性。

Application of Vision Measurement in Hand Eye Calibration of Robot Machining Process

Aiming at the hand eye calibration of high-precision measurement aided robot machining,an accurate hand eye calibration method based on three-dimensional vision measurement was proposed,in which the effects of nonlinear optimization and modeling errors in initial value calculation were considering.In order to improve the accuracy of the solution,a nonlinear calibration model with more accurate reference points was established in the sensor frame,and an iterative weight optimization solution combining sensor measurement and robot position random error was proposed.In the initial value solution,the measurement adjustment model considering the reference measurement error of the base frame was established and solved by Lagrange multiplier.The simulation results show that this method has higher accuracy than other typical methods in estimating hand eye transform parameters.Finally,an experimental platform was built to further verify the superiority of the proposed method in solving accuracy test.