Computer vision for guiding manual assembly

This paper considers an augmented reality interface for guiding manual assembly. The key challenges involved in enabling such a system include the design of an effective information presentation scheme, as well as robust and fast sensing of the assembly scene. We present a framework for assembly scene augmentation that is based on robotic assembly planning. We then discuss the problem of sensing for augmented reality without the use of fiducial and present our formulation that combines model-based and appearance-based approaches for recognizing assembly states.

[1]  Frédéric Jurie Model-based object tracking in cluttered scenes with occlusions , 1997, Proceedings of the 1997 IEEE/RSJ International Conference on Intelligent Robot and Systems. Innovative Robotics for Real-World Applications. IROS '97.

[2]  Azriel Rosenfeld,et al.  3-D Shape Recovery Using Distributed Aspect Matching , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Hiroshi Murase,et al.  Learning and recognition of 3D objects from appearance , 1993, [1993] Proceedings IEEE Workshop on Qualitative Vision.

[4]  Thomas L. DeFazio,et al.  An integrated computer aid for generating and evaluating assembly sequences for mechanical products , 1991, IEEE Trans. Robotics Autom..

[5]  Arthur C. Sanderson,et al.  A correct and complete algorithm for the generation of mechanical assembly sequences , 1991, IEEE Trans. Robotics Autom..

[6]  Michael Georgiopoulos,et al.  Learning geometric hashing functions for model-based object recognition , 1995, Proceedings of IEEE International Conference on Computer Vision.

[7]  Horst Bischof,et al.  Dealing with occlusions in the eigenspace approach , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Suya You,et al.  Natural Feature Tracking for Augmented Reality , 1999, IEEE Trans. Multim..

[9]  Avinash C. Kak,et al.  A robot vision system for recognizing 3D objects in low-order polynomial time , 1989, IEEE Trans. Syst. Man Cybern..

[10]  David G. Lowe,et al.  Indexing without Invariants in 3D Object Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Jun Rekimoto,et al.  Matrix: a realtime object identification and registration method for augmented reality , 1998, Proceedings. 3rd Asia Pacific Computer Human Interaction (Cat. No.98EX110).

[12]  G. Klinker,et al.  A fast and robust line-based optical tracker for augmented reality applications , 1999 .

[13]  J. H. M. Byne,et al.  Surface Based Hypothesis Verification in Intensity Images Using Geometric and Appearance Data , 1998, ACCV.

[14]  Raimund Seidel,et al.  Efficiently Computing and Representing Aspect Graphs of Polyhedral Objects , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Arthur C. Sanderson,et al.  Representations of mechanical assembly sequences , 1991, IEEE Trans. Robotics Autom..

[16]  K. Sengupta,et al.  Using geometric hashing with information theoretic clustering for fast recognition from a large CAD modelbase , 1995, Proceedings of International Symposium on Computer Vision - ISCV.

[17]  Rajeev Sharma,et al.  Real-Time Tracking of Multiple Objects Using Fiducials for Augmented Reality , 2001, Real Time Imaging.

[18]  Emanuele Trucco,et al.  Making good features track better , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[19]  J Ferryman,et al.  LEARNING 3D OBJECT-CENTRED APPEARANCE MODELS FOR TRACKING , 1999 .

[20]  Rajeev Sharma,et al.  Interactive evaluation of assembly sequences using augmented reality , 1999, IEEE Trans. Robotics Autom..

[21]  Subhashis Banerjee,et al.  Isolated 3D object recognition through next view planning , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[22]  Clark F. Olson,et al.  View-Based Recognition Using an Eigenspace Approximation to the Hausdorff Measure , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Clark F. Olson,et al.  A General Method for Feature Matching and Model Extraction , 1999, Workshop on Vision Algorithms.