NSF Award
0339816
This Small Business Innovation Research (SBIR) Phase I project deals with the problems of reconstructing complex freeform shapes from measured data. Of primary interest is the creation of well-structured, high- quality CAD models. Several techniques exist to reach this goal. Unfortunately, automatic surfacing systems provide only rough approximations and do not capture the original design intent, while manual segmentation methods are not very stable and require tedious work. Using the functional decomposition paradigm, objects are built up as a collection of large, independent primary surfaces being connected by smaller, dependent feature surfaces, such as fillets or swept surfaces. This project aims to elaborate semi-automatic methods to build up the topology of the object and compute optimal surface representations for the individual point regions. Emphasis is put on different fairing methods to relocate the segmenting curve network and different constrained surface fitting algorithms to assure smooth connections to existing surface geometry. The proposed research starts with theoretical ground work in geometric modeling, followed by a prototype implementation to prove the feasibility and efficiency of the algorithms.<br/><br/>This technology should significantly shorten lead-time in related industrial design and manufacturing processes and produce more aesthetic objects. The main applications will be product design, including automotive, aerospace, consumer products, and medical devices. The improved product will help US manufacturing industry to be more competitive in the world market by providing a way to introduce design on demand and engineering on demand services. It will also help US companies increase customer-focused production and reduce the time between product iterations.
