Point cloud segmentation method for three-dimensional measurement of complex special-shaped curved surface robot

Abstract

The invention discloses a point cloud segmentation method for three-dimensional measurement of a complex special-shaped curved surface robot, and the method comprises the following steps: S100, inputting a blade point cloud X taking the ground and a desktop as backgrounds, filtering background points through voxel filtering, and obtaining a target blade point cloud Y; S200, calculating a normal vector and a plane profile tolerance of a Y midpoint by utilizing a PCA algorithm, removing outliers, and marking an associated point set as a consistent set CS; s300, establishing paired connection byutilizing the normal vector and the plane profile tolerance deviation, searching after determining a clustering center, and searching all points connected with the clustering center to generate a cluster C; s400, performing curved surface fitting on the cluster C by using a Delaunay triangulation method; s500, for each fitted curved surface slice, calculating the curvature of the curved surface slice, setting a curvature deviation threshold value, and if the curvature deviation between two adjacent curved surface slices is smaller than the threshold value, combining the curved surface slices;otherwise, not combining to obtain a complete leaf point cloud Y separated from the background point cloud. The method has the advantages of being accurate in segmentation, few in input parameters andhigh in robustness.

Description

technical field [0001] The invention relates to the technical field of visual measurement, in particular to a point cloud segmentation method for three-dimensional measurement of a complex special-shaped curved surface robot. Background technique [0002] Complex irregular surface is a kind of surface with unstructured shape, compound curved surface, arbitrary stacking in space, large curvature change and difficult edge detection. Taking aero-engine turbine blades as an example, complex and special-shaped surfaces are widely used in high-end intelligent manufacturing fields such as aerospace and automobile manufacturing. People's demand for how to obtain three-dimensional information and perform precise measurements is increasing. However, the complex special-shaped surface point cloud obtained by 3D vision measurement is unstructured and has many noisy points. As an important preprocessing process for 3D point cloud processing, point cloud segmentation is a key step in 3D ...

AI Technical Summary

Problems solved by technology

This method is simple and easy to implement, but it is too dependent on the selection of seed points or the rules of region growth. It can usually only be used for preliminary semantic segmentation. The refinement process needs to be mixed with other methods, resulting in low accuracy.

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