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IJAT Vol.3 No.6 pp. 760-767
doi: 10.20965/ijat.2009.p0760
(2009)

Paper:

Man-Machine Interface for Human-Robot Collaborative Cellular Manufacturing System

Jeffrey Too Chuan Tan, Feng Duan, Ryu Kato, and Tamio Arai

Arai Laboratory, Intelligent Systems Division, Department of Precision Engineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

Received:
July 1, 2009
Accepted:
August 28, 2009
Published:
November 5, 2009
Keywords:
man-machine interface (MMI), human-robot collaboration, cellular manufacturing system
Abstract

In a human-centered cellular manufacturing system, various machines, including robots, are implemented to support the human operator with the goal of improving overall productivity. In order to ensure the effectiveness of such a system, an effective man-machine interface (MMI) plays an important role in ensuring collaboration and safety, and providing assembly information support. Using a task analysis approach, the assembly operation is broken down into a hierarchical task structure and remodeled for collaboration. In the modeling, appropriate operation properties are extracted as assembly information and, together with reference media in various formats, multimedia support information is produced. The assembly information support is presented on a workbench incorporating a horizontal LCD TV display, and the human operator interacts with the operation control system through a GUI on a touch screen monitor. To ensure collaboration safety, the control system monitors input from safety sensors, an operator safety monitoring system, and robot control. A system performance evaluation study has proven the effectiveness of the system in improving collaborative operation.

Cite this article as:
J. Tan, F. Duan, R. Kato, and T. Arai, “Man-Machine Interface for Human-Robot Collaborative Cellular Manufacturing System,” Int. J. Automation Technol., Vol.3, No.6, pp. 760-767, 2009.
Data files:
References
  1. [1] K. Isa and T. Tsuru, “Cell production and workplace innovation in Japan: Towards a new model for Japanese manufacturing?” Industrial Relations, Vol.41, No. 4, pp. 548-578, 2002.
  2. [2] A. D. Greer, P. M. Newhook, and G. R. Sutherland, “Human-machine interface for robotic surgery and stereotaxy,” IEEE/ASME Trans. on Mechatronics, Vol.13, No.3, pp. 355-361, 2008.
  3. [3] F. Duan, M. Morioka, J. T. C. Tan, and T. Arai, “Multi-modal assembly-support system for cell production,” Int. J. of Automation Technology, Vol.2, No.5, pp. 384-389, 2008.
  4. [4] N. A. Stanton, “Hierarchical task analysis: Developments, applications, and extensions,” Applied Ergonomics, Vol.37, No.1, pp. 55-79, 2006.
  5. [5] E. Helms, R. D. Schraft, and M. Hagele, “rob@work: Robot assistant in industrial environments,” in Proc. of 11th IEEE Int. Workshop on Robot and Human Interactive Communication, pp. 399-404, 2002.
  6. [6] J. P. Thomas, N. Nissanke, and K. D. Baker, “A hierarchical petri net framework for the representation and analysis of assembly,” IEEE Trans. on Robotics and Automation, Vol.12, No.2, pp. 268-279, 1996.
  7. [7] Y. Zhang, F. Duan, J. T. C. Tan, K. Watanabe, N. Pongthanya, M. Sugi, H. Yokoi, and T. Arai, “A study of design factors for information supporting system in cell production,” in The 41st CIRP Conf. on Manufacturing Systems, pp. 319-322, 2008.
  8. [8] R. E. Mayer, “Multi-media learning,” New York: Cambridge University Press, 2001.
  9. [9] F. Duan, J. T. C. Tan, and T. Arai, “Using motion capture data to regenerate operator's motions in a simulator in real time,” in Proc. of the IEEE Int. Conf. on Robotics and Biomimetics, pp. 102-107, 2008.

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Last updated on Nov. 18, 2019