Design and error analysis of a dual-degree-of-freedom 3d scanner based on laser range sensdors

Abstract 3D scanning, measurement, and reconstruction have wide-ranging applications in industrial fields, medical devices, and cultural heritage preservation. This study focuses on the field of 3D measurement and reconstruction, proposing a dual-degree-of-freedom layer-by-layer 3D scanner based on the principle of optical reflection. The scanner employs a laser range sensor to perform layered scanning through a linear motion guide and a translational-rotary platform driven by stepper motors. To improve the computational efficiency of the ICP algorithm, the Newton iteration method is employed to apply global rotation and translation to the sampled point cloud, optimizing the accuracy of point cloud registration. The scanned objects are categorized into three types based on whether the surfaces of their spatial geometries are second-order differentiable. The final matching results show an RMSE range of 0.2–0.7 and a residual variance range of 0.02–0.31, indicating that the RMSE meets the requirements of 3D reconstruction according to international standards. Experimental results demonstrate that the proposed 3D scanner achieves high-precision scanning and reconstruction capabilities, and the surface characteristics of the scanned objects significantly influence the measurement results. The analysis of error distribution provides theoretical guidance for further optimizing device performance and algorithm accuracy.