SBIR-STTR Award

Creating Functionally Decomposed Surface Models from Measured Data
Award last edited on: 5/12/2005

Sponsored Program
SBIR
Awarding Agency
NSF
Total Award Amount
$589,179
Award Phase
2
Solicitation Topic Code
-----

Principal Investigator
Lazhu Wang

Company Information

Raindrop Geomagic Inc (AKA: Geomagic Inc)

Po Box 12219
Research Triangle Pk, NC 27709
   (919) 474-0122
   inquiry@geomagic.com
   www.geomagic.com
Location: Single
Congr. District: 04
County: Durham

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2003
Phase I Amount
$100,000
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. 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

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
2004
Phase II Amount
$489,179
This Small Business Innovation Research Phase II project deals with the problems of reconstructing complex free-form shapes from measured data. Raindrop Magic's primary interest is to produce 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 functional decomposition, 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. In Phase I, semi-automatic methods were elaborated to create good segmenting curve nets. Exploiting the specific properties of different feature types, the research team proposed algorithms to compute optimal surface representations for each. In Phase II, the team envisions transforming and extending their theoretical results into robust and efficient computational algorithms. Five subsystems are proposed: Surface-Indicators, Constrained-Fitting, Curve-Tracing, Fairing, and Feature-Fitting. New core technologies are developed for creating different geometric entities, which are eventually integrated to obtain high-quality surface models. This technology should significantly shorten lead-time in related industrial design and manufacturing processes and produce aesthetic objects, having a positive impact on the whole society. The proffered technology has broader impacts in two key market sectors: reverse engineering and advanced surfacing. At the research front, the proposed project deepens the understanding of computer-aided geometric modeling working with scan data, a field that has not received much attention from the large CAD companies, but is an active area of research. It combines the knowledge of both discrete and continuous mathematics and takes advantage of the strength of both approaches. On the technology front, it introduces a new paradigm that will significantly improve the current commercial systems of reverse engineering with better engineering features and advanced surfacing through simpler operations. The main applications will be product design, including automotive, aerospace, consumer products, and medical devices. The improved product will help the US manufacturing industry to be more competitive in the world market, providing a way to introduce design on demand and engineering on demand services. The proposed project will help US companies to increase customer-focused production and reduce the time between product iterations