CAD-Based 3D Object Representation for Robot Vision

This article explains that most existing vision systems rely on models generated in an ad hoc manner and have no explicit relation to the CAD/CAM system originally used to design and manufacture these objects. The authors desire a more unified system that allows vision models to be automatically generated from an existing CAD database. A CAD system contains an interactive design interface, graphic display utilities, model analysis tools, automatic manufacturing interfaces, etc. Although it is a suitable environment for design purposes, its representations and the models it generates do not contain all the features that are important in robot vision applications. In this article, the authors propose a CAD-based approach for building representations and models that can be used in diverse applications involving 3D object recognition and manipulation. There are two main steps in using this approach. First, they design the object's geometry using a CAD system, or extract its CAD model from the existing database if it has already been modeled. Second, they develop representations from the CAD model and construct features possibly by combining multiple representations that are crucial in 3D object recognition and manipulation.

[1]  Katsushi Ikeuchi Generating an interpretation tree from a CAD model to represent object configurations for bin-picking tasks , 1986 .

[2]  Azriel Rosenfeld,et al.  Decomposition and approximation of three-dimensional solids , 1986, Comput. Vis. Graph. Image Process..

[3]  I. Faux,et al.  Computational Geometry for Design and Manufacture , 1979 .

[4]  I. Biederman Human image understanding: Recent research and a theory , 1985, Computer Vision Graphics and Image Processing.

[5]  Bir Bhanu,et al.  RANGE DATA PROCESSING: REPRESENTATION OF SURFACES BY EDGES. , 1986 .

[6]  Charles R. Dyer,et al.  Model-based recognition in robot vision , 1986, CSUR.

[7]  Bir Bhanu,et al.  CAGD based 3-D vision , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[8]  Bir Bhanu,et al.  3-D model building for computer vision , 1987, Pattern Recognit. Lett..

[9]  Berthold K. P. Horn Extended Gaussian images , 1984, Proceedings of the IEEE.

[10]  Tom Lyche,et al.  Discrete B-splines and subdivision techniques in computer-aided geometric design and computer graphics , 1980 .

[11]  Bir Bhanu,et al.  Representation and Shape Matching of 3-D Objects , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[12]  Bir Bhanu,et al.  Intrinsic characteristics as the interface between CAD and machine vision systems , 1985, Pattern Recognit. Lett..

[13]  ARISTIDES A. G. REQUICHA,et al.  Representations for Rigid Solids: Theory, Methods, and Systems , 1980, CSUR.

[14]  Ramesh C. Jain,et al.  Invariant surface characteristics for 3D object recognition in range images , 1985, Comput. Vis. Graph. Image Process..

[15]  Kristhan T. Gunnarsson,et al.  CAD Model-Based Localization of Parts in Manufacturing , 1987, Computer.

[16]  S. Shafer Shadows and Silhouettes in Computer Vision , 1985 .

[17]  Ramakant Nevatia,et al.  Description and Recognition of Curved Objects , 1977, Artif. Intell..