Automatic Data Segmentation and Geometric Reasoning of Unorganized Point Cloud for Reverse Engineering of Precision Mechanical Objects

Ohio State University Research Foundation -Do Not Use, Columbus OH

Investigators

Abstract

This grant provides funding for the development of the necessary technologies that support automatic geometric model reconstruction of existing objects having arbitrary topology when the prototype is created or modified on the shop floor and when a computer-aided design model does not exist. Particularly, the focus is to automate the data segmentation process on the reconstructed manifold surface and to facilitate optimal geometric model reconstruction for precision mechanical parts by geometric computation and reasoning. An algorithm will be developed to efficiently reconstruct a triangle mesh from 3-dimensional unorganized coordinate points to optimally recover the object shape. The reconstructed triangle mesh captures object topology with the associated 2-manifold represented as a combinatorial structure, which establishes explicit relations among the data points, and provides a topological domain with necessary differential geometric characteristics for the subsequent data segmentation process. By extending segmentation concepts from the regular image domain to the irregular mesh domain, a robust two-step automatic data segmentation approach will be developed, combining the border-based approach and the region growing approach. Finally, algorithms for geometric computation and reasoning will be developed to automatically classify the segmented patches into surface elements and to infer possible topological relations and geometric constraints among them. If successful, the results of this research will lead to significant improvements in automatic geometric model reconstruction and reverse engineering. With automatic data segmentation and intelligent geometric reasoning, user intervention can be eliminated and the entire model reconstruction process can be shortened from days to minutes. When integrated with state of the art scanning devices, the developed technologies could lead to a seamless reverse engineering process and support rapid design and prototyping of high-precision mechanical components. The results will have potential application in a whole spectrum of engineering problems with a major impact on rapid design and prototyping, shape analysis, and virtual reality.