To improve the assembly accuracy of intelligent assembly process, a 3D surface reconstruction system based on laser scanning for assembly targets and assembly positions was designed. The light source uses a line laser to provide structured light, enabling rapid scanning of the assembly target surface on a single line. Calculate the spatial relationship between the assembly target and the assembly position through the calibration board. A position inversion optimization algorithm has been proposed. By completing the transformation of feature points from local coordinates to global coordinates. The energy distribution in the central area of the CCD image plane was simulated and analyzed under different baseline lengths, and the optimal baseline position of 35 mm was determined. The experiment is divided into two parts, and the reconstruction of the three-dimensional surface of the free-form surface target based on laser scanning was completed in the laboratory. The optimized target 3D point cloud data is evenly distributed, with almost no scattered points on the main two local surfaces, which well reflects the surface structure of the target. In the actual outdoor assembly experiment, the system cooperated with the assembly vehicle to achieve the correct assembly of the assembly. The reconstruction accuracy deviation of most test points is very small, with over 85% of test points having an error of less than 0.54 mm. The average deviation of these points before and after optimization is 0.67 mm. This system has higher application value in the field of large-scale intelligent assembly.
