Design Intent Detection

Reverse engineering creates a CAD model of an object from 3D measurements obtained, e.g., by a 3D laser scanner. Such models do not contain any information about their design intent: intended regularities, such a symmetries, congruencies between sub-parts or a construction sequence for the model, etc. are not explicitly recorded. Furthermore, such models are approximate due to measurement errors and approximation and numerical errors from the reconstruction process. Similarly, for data exchange, transferring a model from one CAD system into another usually does not transfer design intent and may also result in approximate models due to different model representations and tolerance systems. This makes it hard for engineers to meaningfully modify or analyse such models.

For this project we devised novel algorithms to detect design intent automatically in CAD models of engineering objects in terms of intended geometric relationships between a model’s vertices, edges, faces and sub-parts, and their properties. Especially symmetries are a key concept for design intent detection as engineering objects often exhibit symmetries and related regularities for functional, aesthetic and manufacturing reasons.


  • Design Intent Detection

    Our approach is based on two ideas: (1) decomposing a model into suitable sub-parts simplifies finding regularities, which are less ambiguous compared to analysing the model as one part; and (2) detecting approximate symmetries and related regularities reveals a likely design intent description, but requires careful handling of tolerances to reduce the inconsistency between the ...

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    Publications

    • M. Li, F. C. Langbein, R. R. Martin. Detecting Design Intent in Approximate CAD Models Using Symmetry. Computer-Aided Design, 42(3):183-201, 2010.

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    • F. C. Langbein, M. Li, R. R. Martin. A Comment on ‘Constructing Regularity Feature Trees for Solid Models’. In: Advances in Geometric Modeling and Processing, Proc. Geometric Modelling and Processing, Springer LNCS, 4975:603, 2008.

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    • M. Li, F. C. Langbein, R. R. Martin. Detecting Approximate Symmetries of Discrete Point Subsets. Computer-Aided Design, 40(1):76-93, 2008.

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    • M. Li, F. C. Langbein, R. R. Martin. Detecting Approximate Incomplete Symmetries in Discrete Point Sets. In: Proc. ACM Symp. Solid and Physical Modeling, pp. 335-340, ACM Siggraph 2007.

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    • M. Li, X.-S. Gao, S.-C. Chou. Quadratic Approximation to Plane Parametric Curves and its Application in Approximate Implicitization. The Visual Computer, 22(9-11):906-917, 2006.

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    • M. Li, F. C. Langbein, R. R. Martin. Constructing Regularity Feature Trees for Solid Models. In: M.-S. Kim, K. Shimada (eds), Proc. Geometric Modeling and Processing, Springer LNCS, 4077:267-286, 2006.

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    Presentations

    • F. C. Langbein. Reverse Engineering: From Artifacts to Concepts. Public engagement and outreach talk given at various occasions.

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    • F.C. Langbein. Design Intent of Geometric Models. Invited seminar talk, Institute of Information and Mathematical Sciences, Massey University at Albany, 22nd September 2004.

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    • F. C. Langbein. Design Intent of Geometric Models. Invited seminar talk, Dept. Computer Science, Auckland University, 15th September 2004.

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    • FC Langbein. Design Intent of Reverse Engineered Geometric Models. Dept. Computer Science, Cardiff University, 17th July, 2002.

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    Codes

      Engagement

      • F. C. Langbein. Reverse Engineering: From Artifacts to Concepts. Public engagement and outreach talk given at various occasions.

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      Partners

      • Ming Li
        State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou, China.

      • Ralph R Martin
        School of Computer Science and Informatics, Cardiff University, Cardiff, UK.

      • Frank C Langbein
        School of Computer Science, Cardiff University, Cardiff, UK.

      Funding

      • July 2004 – July 2007: Detection of Design Intent in Complex Approximate Geometric Models. EPSRC GR/S69085/01. PI: F. C. Langbein. £123,639.

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      Miscellaneous