This study aims to address the calibration of the installation orientation between the sensor and the motion platform in line-structured light measurement systems. By developing a high-precision and robust calibration method, it seeks to improve the overall accuracy and reliability of three-dimensional topography measurements for complex surfaces.
A three-dimensional stereoscopic target is adopted as the calibration reference, and an ellipse contour fitting optimization algorithm based on the boxplot method is proposed. This algorithm is used to accurately extract the elliptical contours of the feature holes on the target and optimize their fitting process. By processing the collected contour data with this algorithm, an accurate mapping relationship between the laser beam direction of the sensor and the direction of the motion platform is established, thereby achieving high-precision calibration of the system’s orientation parameters.
Experimental results demonstrate that the proposed calibration method can effectively identify and suppress gross errors in the contour data, enabling stable ellipse contour fitting. Based on this method, the system successfully calibrates the laser beam direction of the line-structured light sensor and the motion platform direction, providing a more accurate spatial reference for three-dimensional topography measurements.
The main contribution of this paper lies in introducing the boxplot method into the ellipse contour fitting process, constructing a fitting optimization algorithm with robustness against gross errors. This method not only improves the robustness and accuracy of ellipse center extraction, but also offers a new, cost-effective and easy-to-implement approach for calibrating line-structured light systems, which holds certain value for engineering applications.
