PIN tip extraction from 3D point cloud of structured light

In industrial production, there is a higher precision requirement for pin detection. In view of the burr phenomenon, holes, outliers and a large number of different types of noise in point cloud da ta, this paper proposes a method to extract the pin tip plane in three-dimensional space using structured light technology. First of all, rough extraction of point cloud is carried out by geometric characteristics and through filtering. It can locate the target point cloud quickly and remove a large number of non-target point clouds and outliers accurately. Then, the target point cloud is indexed by KD-tree, the Euclidean distance clustering segmentation algorithm is used to segment the number of point clouds. It can stably and effectively remove small-scale noise near the target point cloud. Finally, the angle is judged between the vector of the target point cloud and the normal vector of the reference plane. It can remove the uneven noise in the target point cloud effectively and accurately. The experimental results show that this method can not only remove the noise of the pin point cloud data accurately, but also extract the pin point coordinates accurately. The standard deviation of the pin height measurement in different directions is within 0.005 mm. The method proposed in this paper is generally applicable to the extraction of flat pin tip with high precision, high speed and good robustness.