| Popis: |
With the development of the manufacturing industry, the required parts are gradually moving towards larger sizes, complex shapes, and high surface processing quality. Moreover, detecting the quality of parts during the processing is an essential step. In order to improve the accuracy, the speed and the automation of quality inspection, the 3D inspection based on model analysis has replaced the traditional manual inspection and the 2D inspection, and becomes an important means in the field of industrial inspection. The accuracy of point cloud registration, as a key part of 3D inspection, directly affects the accuracy of detection results. Therefore, the main research achievements of scholars at home and abroad in point cloud registration technology are summarized. Based on algorithm principles, the current registration methods are summarized into traditional registration methods, registration methods based on affine swarm intelligent optimization algorithms, and registration methods based on deep learning. The characteristics, the advantages and the disadvantages, the typical algorithms and their variants of each method are introduced in detail. The technical difficulties of point cloud registration are summarized and the future development trend is prospected. |
