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IJAT Vol.3 No.4 pp. 465-470
doi: 10.20965/ijat.2009.p0465
(2009)

Paper:

High-Accuracy and Low-Cost Chamfering System by a Material-Handling Robot –Individual Error Compensation Using Image Processing–

Naoki Asakawa*, Hidetake Tanaka**, Tomoya Kiyoshige*,
and Masatoshi Hirao*

*Graduate School of Natural Science and Technology, Kanazawa University, Kakuma-machi, Kanazawa, Ishikawa 920-1192, Japan

**Faculty of Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka, Nagaoka, Niigata 940-2188, Japan

Received:
January 20, 2009
Accepted:
April 22, 2009
Published:
July 5, 2009
Keywords:
industrial robot, chamfering, image processing, error compensation
Abstract
The study deals with an automation of chamfering by a material-handling robot with considering of accuracy and costs. The study focused on automation of chamfering without influence of individual dimensional error of workpiece. A casted impeller usually chamfered with handwork is treated in the study as an example of a workpiece having individual dimensional error. In the system, a file driven by air reciprocating actuator is used as a chamfering tool and image processing technology is used to compensate the dimensional error of the workpiece. The robot hand carries a workpiece instead of a chamfering tool both for chamfering and for material handling. From the experimental result, the system is found effective to chamfer a workpiece having dimensional error automatically.
Cite this article as:
N. Asakawa, H. Tanaka, T. Kiyoshige, and M. Hirao, “High-Accuracy and Low-Cost Chamfering System by a Material-Handling Robot –Individual Error Compensation Using Image Processing–,” Int. J. Automation Technol., Vol.3 No.4, pp. 465-470, 2009.
Data files:
References
  1. [1] K. G. Ahn and D. W. Cho, “An analysis of the volumetric error uncertainty of a three-axis machine tool by beta distribution,” International Journal of Machine Tools and Manufacture, Vol.40, No.15, pp. 2235-2248, 2000.
  2. [2] E. L. J. Bohez, “Compensating for systematic errors in 5-axis NC machining,” Computer-Aided Design, Vol.34, No.5, pp. 391-403, 2002.
  3. [3] G. Alicia, and B. Shirinzadeh, “A systematic technique to estimate positioning errors for robot accuracy improvement using laser interferometry based sensing,” Mechanism and Machine Theory, Vol.40, No.8, pp. 879-906, 2005.
  4. [4] J.-H. Jung, J.-P. Choi, and S.-J. Lee, “Machining accuracy enhancement by compensating for volumetric errors of a machine tool and on-machine measurement,” Journal of Materials Processing Technology, Vol.174, No.1-3, pp. 56-66, 2006.
  5. [5] N. Asakawa, Y. Mizumoto, and Y. Takeuchi, “Automation of Chamfering by an Industrial Robot; Development of a System with Reference to Tool Application Direction,” Journal of Robotics and Mechatronics, Vol.13, No.1, pp. 30-35, 2001.
  6. [6] N. Asakawa, Y. Mizumoto, and Y. Takeuchi, “Automation of Chamfering by an Industrial Robot; Improvement of a System with Reference to Tool Application Direction,” Proc. of the 35th CIRP Int. Seminer on Manufacturing Systems, pp. 529-534, 2002.
  7. [7] H. Tanaka, N. Asakawa, and M. Hirao, “Control of Chamfering Quality by an Industrial Robot,” Proc. of Int. Conf. on Machine Automation 2002, pp. 399-346, 2002.
  8. [8] T. Nakajima, S. Aoyagi, and M. Takano, “Automation of Personal Computer Disassembling Process Based on RECS,” Proc. of Int. Conf. on Machine Automation 2002, pp. 139-146, 2002.
  9. [9] K. Shirase, N. Tanabe, M. Hirao, and T. Yasui, “Articulated robot application in end milling of sculptured surface,” JSME Int. Journal, Series C, Vol.39, No.2, pp. 308-316, 1996.
  10. [10] A. C. Okafor and Y. M. Ertekin, “Derivation of machine tool error models and error compensation procedure for three axes vertical machining center using rigid body kinematics,” Vol.40, No.8, pp. 1199-1213, 2000.
  11. [11] Ph. Drouet, S. Dubowsky, S. Zeghloul, and C. Mavroidis, “Compensation of geometric and elastic errors in large manipulators with an application to a high accuracy medical system,” Robotica, Vol.20, No.3 , pp. 341-352, 2002.
  12. [12] G. M. Bone and D. Capson, “Vision-guided fixtureless assembly of automotive components,” Robotics and Computer-Integrated Manufacturing, Vol.19, No.1-2, pp. 79-87, 2003.
  13. [13] A. Watanabe, S. Sakakibara, K. Ban, M. Yamada, G. Shen, and T. Arai, “A Kinematic Calibration Method for Industrial Robots Using Autonomous Visual Measurement,” CIRP Annals - Manufacturing Technology, Vol.55, No.1, pp. 1-6, 2006.
  14. [14] FANUC Integrated Vision Function iRVision,
    http://www.fanuc.co.jp/en/product/robot/intelligence/irvision.html
  15. [15] Jef Poskanzer: The PNM Format,
    http//netpbm.sourceforge.net/doc/pnm.html

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