Abstract
In spite of decades of work on object recognition in both the academic and industrial communities, the majority of industrial robotic applications are not vision guided, relying instead on mechanical fixturing and dead reckoning. The primary reason for this is that object recognition by machine vision simply has not worked well enough to be competitive. Recent developments in object recognition algorithms, driven by increasing demand for flexible automation and enabled by processor architectures well-suited to image analysis, have begun to change this picture. We will discuss requirements that must be satisfied for a method to achieve widespread use, trace the development of industrial object recognition, describe the present method, and mention some applications. Throughout we offer industrial perspective and experience to an academic forum, in hopes of better understanding.
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References
Grimson W.E.L., 1990, Object Recognition by Computer. M. I. T. Press, Cambridge.
Marr D., 1982, Vision. W.H. Freeman & Co., New York.
Havelock D.I., 1989, Geometric Precision in Noise-Free Digital Images. IEEE Trans. Patt. Anal & Mach. Intell., vol. 11, no. 10., pp. 1065–1075.
O’Gorman L., 1996, Subpixel Precision of Straight-Edged Shapes for Registration and Measurement. IEEE Trans. Patt. Anal. and Mach. Intell., vol. 18, no. 7., pp. 746–751.
Horn B.K.P., 1986, Robot Vision. MIT Press, Cambridge.
Roth, S.D., 1989, Vision System for Distinguishing Touching Parts. U.S. Patent #4, 876, 728.
Silver W.M., 1987, Normalized Correlation Search in Alignment, Gauging, and Inspection. Proc. SPIE, vol. 755, pp. 23–34.
Silver W.M., R.A. Wolff, R.E. Dynneson, 1990, Digital Image Processing System. U.S. Patent #4, 972, 359.
McGarry J., 1991, Acumen 900 Series News Release. October 22, 1991.
Hough P.V.C., 1962, Method and means for recognizing complex patterns. U.S. Patent #3,069,654.
Ballard D.H., C.M. Brown, 1982, Computer Vision. Prentice-Hall, Englewood Cliffs, N.J.
Lubofsky E., 1999, Machine Vision Streamlines Robotic Handling of Engine Parts. Robotics World, March/April 1999, pp. 20–25.
Staff Writer, 1999, Vision Tech. Improves Robotic Part Loading. Manufacturing Engineering, March 1999, pp. 154–156.
Machine Design, March 11, 1999, p. 176.
ABB Flexible Automation, 1998, FlexPicker IRB 340 Industrial Robot product brochure.
Staff Writer, 1999, Ford automates engine block loading process with machine vision. Automotive Engineering International, February.
Quality, April 1999, pp. 120–121.
Staff Writer, 1999, Rim Shot. Manufacuring Automation, March/April.
Murphy W.B., 1999, Tire Tread Recognition. Proc. 1999 International Robots & Vision Conference, Automated Imaging Association.
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© 2000 Springer-Verlag London
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Silver, W. (2000). Geometric Pattern Matching for Industrial Robot Guidance. In: Hollerbach, J.M., Koditschek, D.E. (eds) Robotics Research. Springer, London. https://doi.org/10.1007/978-1-4471-0765-1_9
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DOI: https://doi.org/10.1007/978-1-4471-0765-1_9
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1254-9
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