Research on the Visual Guidance System of Zoning Casting Grinding Based on Feature Points

Abstract

Compared to traditional rough casting grinding (RCG), the individualization of castings is very different, which makes it difficult to realize the automation of casting grinding. At this stage, the primary method is manual grinding. In this study, the regional casting grinding system based on feature points is adopted to achieve the personalized grinding of castings and improve the grinding efficiency and the automation level of the manufacturing process. After preprocessing the point cloud, the fast point feature histogram (FPFH) descriptor is used to describe the features of each region and construct the local template. The position of the local region is obtained by template matching. The random sample consensus (RANSAC) algorithm is used to calculate the plane and fit the point cloud to obtain the contact point trajectory of the grinding head. Then, according to different polishing methods, different polishing poses are generated. The simulation experimental results show that the system has good adaptability, and the consistency of finished products is good.