Positioning errors are a primary performance indicator of precision stages. Calibration of stage positioning errors usually requires expensive, specialised instruments or artefacts. In this paper, we introduce a simple and cost-effective, machine vision-based method for stage error calibration. The novelty is that we used an arbitrarily textured plane, for example an array of coins, as the imaging target, as opposed to costly precision machined artefacts. Positioning errors were extracted from overlapped texture images using a fast and globally optimised feature-matching algorithm. A computer simulation demonstrates that the method is accurate and numerically stable in terms of sensing noise. Trials with a coordinate measuring machine reveal that the method can achieve sub-pixel accuracy, with a maximum measurement error of approximately 3 μm within a 100 mm range.

定位误差是精密载物台的主要性能指标。平台定位误差的校准通常需要昂贵的专用仪器或人工制品。在本文中，我们介绍了一种简单且经济高效的基于机器视觉的平台误差校准方法。新颖之处在于，我们使用了任意纹理的平面，例如一排硬币，作为成像目标，而不是昂贵的精密加工制品。使用快速且全局优化的特征匹配算法从重叠纹理图像中提取定位误差。计算机模拟表明，该方法在感测噪声方面是准确且数值稳定的。用坐标测量机进行的试验表明，该方法可以达到亚像素精度，