Top > JRM > Visually Guided Microassembly with Active Zooming

single-rb.php

JRM Vol.18 No.6 pp. 787-794
doi: 10.20965/jrm.2006.p0787
(2006)

Paper:

Views over last 60 days: 463

Visually Guided Microassembly with Active Zooming

Xiaodong Tao*, Hyungsuck Cho*, and Youngjun Cho**

*Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, 373-1, Guseong-dong, Yuseong-dong, Daejeon, Korea

**Mechatronics Team, Korea Institute of Industrial Technology (KITECH), Chungnam, Chunan-Si, Korea

Received:
April 5, 2006
Accepted:
August 14, 2006
Published:
December 20, 2006
Creative Commons License
Keywords:
microassembly, visual servoing, active zooming
Abstract
Vision techniques used in automatic microassembly are limited by inherent problems such as small depth of focus and small field of view. Microassembly must, however, initially detect microparts in a wide field of view and large depth of field while maintaining high resolution. We propose microassembly using active zooming that can overcome these limitations. For a small field of view, active zooming prevents the target from getting out of the field of view during microassembly. For a small depth of focus, our proposal is based on focus measure to maintain clear target image in the field of view during microassembly. Two-step assembly thus ensures zoom microscopy maintaining a wide field of view and large depth of field initially and high resolution at the end. Peg-in-hole assembly experiments confirmed the feasibility of our proposal.
Cite this article as:
X. Tao, H. Cho, and Y. Cho, “Visually Guided Microassembly with Active Zooming,” J. Robot. Mechatron., Vol.18 No.6, pp. 787-794, 2006.
Data files:
References
  1. [1] S. J. Ralis, B. Vikaramadiya, and B. J. Nelson, “Micropositioning of a Weakly Calibrated Microassembly System Using Coarse-to-Fine Visual Servoing Strategies,” IEEE Transactions on Electronics Packaging Manufacturing, Vol23, No.2, pp. 123-131, 2000.
  2. [2] B. Vikramaditya, J. B. Lor, and B. J. Nelson, “Visually Servoed Micropositioning for Assembly of Hybrid MEMS: Theory and Experiments,” Proceedings of the 36th Conference on Design & Control, pp. 96-101, 1997.
  3. [3] J. T. Feddema and R. W. Smon, “CAD-Driven Microassembly and Visual Servoing,” IEEE International Conference on Robotics & Automation, Leuven, Beligum, pp. 1212-1219, 1998.
  4. [4] S. Fatikow, J. Seyfried, St. Fahlbusch, A. Buerkl, and F. Schmoeckel, “A Flexible Microrobot-Based Microassembly station,” Journal of intelligent & robotics system, Vol.27, No.1/2, pp. 135-169, 2000.
  5. [5] G. Yang, J. A. Gaines, and B. J. Nelson, “Optomechatronic design of microassembly systems for manufacturing hybrid Microsystems,” IEEE transactions on industrial electronics, Vol.52, No.4, pp. 1013-1023, October 2, 2005.
  6. [6] J. Y. Zheng, T. Sakai, and N. Abe, “Guiding robot motion using zooming and focusing,” Intelligent Robots and Systems, IROS 96, Vol.3, pp. 1076-1082, 1996.
  7. [7] K. S. Choi, J. S. Lee, and S. J. Ko, “New autofocusing technique using the frequency selective weighted median filter for video cameras,” IEEE Transactions on Consumer Electronics, Vol.45, Issue 3, pp. 820-827, Aug., 1999.
  8. [8] O. Faugeras, “Three-Dimensional Computer Vision,” The MIT Press, Cambridge, Massachusetts, London, England.
  9. [9] B. Potsaid, Y. Bellouard, and J. Wen, “Adaptive Scanning Optical Microscope (ASOM): A multidisciplinary optical microscope design for large field of view and high resolution imaging,” Opt. Express 13, pp. 6504-6518, 2005.
  10. [10] J. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Analysis and Machine Intelligence 8(6), pp. 679-698, 1988.
  11. [11] M. A. Fischler and R. C. Bolles, “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography,” Comm. of the ACM, Vol.24, pp. 381-395, 1981.
  12. [12] P. Bouthemy, “A maximum likelihood framework for determining moving edges,” IEEE Trans on Pattern Analysis and Machine intelligence, 11(5), pp. 499-511, 1989.
  13. [13] R. G. Brown and P. Y. C. Hwang, “Introduction to Random Signals and Applied Kalman Filtering with Matlab Exercises and Solutions,” 3rd Edition, Wiley, 1996.
  14. [14] G. D. Hager and S. Hutchinson, “A Tutorial on Visual Servo Control,” IEEE Transactions on Robotics and Automation, Vol.12, No.5, pp. 651-670, 1996.

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

Copyright© 2006 by Fuji Technology Press Ltd. and Japan Society of Mechanical Engineers. All right reserved.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Sep. 06, 2024