电流计
投影(关系代数)
计算机视觉
三维投影
人工智能
激光扫描
计算机科学
扫描仪
结构光三维扫描仪
过程(计算)
激光器
光学
算法
图像(数学)
物理
操作系统
作者
Ziqi Xu,Xuechao Duan,Yue Zhu,Dan Zhang
出处
期刊:Machines
[MDPI AG]
日期:2023-02-02
卷期号:11 (2): 215-215
被引量:4
标识
DOI:10.3390/machines11020215
摘要
A laser projection positioning technique for large composite production based on a scanning galvanometer is proposed in this paper. First, based on the projecting model of the scanning galvanometer, a solution is proposed for the problem which includes pose calculations of the galvanometer projection and autocorrection technology. Then, according to the solution of the perspective-n-point (PNP) problem in the control software for the pose of the scanning galvanometer relative to the projection object, an improved genetic algorithm is proposed to optimize the results of calculating the pose. Meanwhile, to account for the tangential distortion caused by the perturbation between the scanning galvanometer and the projected object during the actual manufacturing process, the projection pattern is corrected by the perspective transform method, thus ensuring the accuracy of the projection. Eventually, in order to evaluate the proposed method, a general scheme of the projection positioning system is designed, and software is developed for the projection device relative to the pose calibration of the composite material mold and projection image correction. Following that, 3D printing model projection experiment and the large composite layup projection positioning tests are conducted with the experimental prototype of the projection positioning system. The result of the 3D printing model projection experiment shows that the calculating accuracy of the relative pose based on the improved adaptive genetic algorithm achieves 0.0007 mm, which is superior to the 1.115 mm accuracy of the solution of photographing the target with the camera. In addition, after a small deformation of the mold in the actual working conditions, the influence of the target localization point in the PNP problem in 2D and 3D coordinates on the algorithm is compared, and the optimized errors are respectively scaled to 2 mm and 0.2 mm. These numerical simulations and experimental results in working conditions show that the proposed method has high accuracy, high robustness, and fast astringency, and it provides a candidate for projection positioning of large composite material layups.
科研通智能强力驱动
Strongly Powered by AbleSci AI