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JRM Vol.24 No.3 pp. 441-451
doi: 10.20965/jrm.2012.p0441
(2012)

Paper:

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Design and Application of an Intelligent Robotic Gripper for Accurate and Tolerant Electronic Connector Mating

Fei Chen*1, Kosuke Sekiyama*1, Baiqing Sun*2, Pei Di*1, Jian Huang*3, Hironobu Sasaki*4, and Toshio Fukuda*1

*1Department of Micro-Nano Systems Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan

*2School of Electrical Engineering, Shenyang University of Technology, Shenyang, Liaoning 110870, China

*3Department of Control Science and Engineering, Huazhong University of Science and Technology Wuhan, Hubei 430074, China

*4Factory Automation Technology Development, Canon Inc., 70-1 Yanagi-cho, Saiwai-ku, Kawasaki-shi, Kanagawa 212-8602, Japan

Received:
October 18, 2011
Accepted:
December 15, 2011
Published:
June 20, 2012
Creative Commons License
Keywords:
robotic hand, sensor, fault detection and diagnosis, hybrid assembly cell
Abstract
In electronic manufacturing systems, the design of the robotic hand is important for successful accomplishment of the assembly task, and also for human and robot coworker coordinated assembly. Due to the restrictions on the architecture of traditional robotic hands, the status of assembly parts, such as position and rotation during the assembly process cannot be detected effectively. In this research, an intelligent robotic hand – i-Hand, equipped with multiple small sensors – is designed and built for this purpose. Mating connectors by robot, as an experimental case in this paper, is studied to evaluate i-Hand performance. A new model that converts the traditional time-zone-driven model to an event-driven model is proposed to describe the process ofmating connectors, within which, most importantly, the distance between the connector and deformable Printed Circuit Board (PCB) is detected by i-Hand. The generated curve has provided more robust parameters than our previously studied Fault Detection and Diagnosis (FDD) classifier. Various possible situations during assembly are considered and handled based on this event-driven work flow. The effectiveness of our proposed model and algorithm is proven in experiments.
Cite this article as:
F. Chen, K. Sekiyama, B. Sun, P. Di, J. Huang, H. Sasaki, and T. Fukuda, “Design and Application of an Intelligent Robotic Gripper for Accurate and Tolerant Electronic Connector Mating,” J. Robot. Mechatron., Vol.24 No.3, pp. 441-451, 2012.
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References
  1. [1] A. Bannat, T. Bautze, M. Beetz, J. Blume, K. Diepold, C. Ertelt, F. Geiger, T. Gmeiner, T. Gyger, A. Knoll et al., “Artificial Cognition in Production Systems,” IEEE Trans. on Automation Science and Engineering, Vol.8, No.1, pp. 148-174, 2011.
  2. [2] F. Chen, K. Sekiyama, J. Huang, B. Sun, H. Sasaki, and T. Fukuda, “An Assembly Strategy Scheduling Method for Human and Robot Coordinated Cell Manufacturing,” Int. J. of Intelligent Computing and Cybernetics, Vol.4, No.4, pp. 487-510, 2011.
  3. [3] J. Krüger, T. Lien, and A. Verl, “Cooperation of Human and Machines in Assembly Lines,” CIRP Annals-Manufacturing Technology, Vol.58, No.2, pp. 628-646, 2009.
  4. [4] J. Tan, F. Duan, Y. Zhang, R. Kato, and T. Arai, “Task modeling approach to enhance man-machine collaboration in cell production,” In IEEE Int. Conf. on Robotics and Automation 2009 (ICRA’09), pp. 152-157, IEEE, 2009.
  5. [5] D. Sun and J. Mills, “Manipulating rigid payloads with multiple robots using compliant grippers,” IEEE/ASME Trans. on Mechatronics, Vol.7, No.1, pp. 23-34, 2002.
  6. [6] A. Pettersson, T. Ohlsson, S. Davis, J. Gray, and T. Dodd, “A Hygienically Designed Force Gripper for Flexible Handling of Variable and Easily Damaged Natural Food Products,” Innovative Food Science & Emerging Technologies, 2011.
  7. [7] A. Bertetto and M. Ruggiu, “A two degree of freedom gripper actuated by SMA with flexure hinges,” J. of Robotic Systems, Vol.20, No.11, pp. 649-657, 2003.
  8. [8] H. Choi andM. Koē, “Design and feasibility tests of a flexible gripper based on inflatable rubber pockets,” Int. J. of Machine Tools and Manufacture, Vol.46, No.12-13, pp. 1350-1361, 2006.
  9. [9] D. Pham and S. Yeo, “Strategies for gripper design and selection in robotic assembly,” Int. J. of production research, Vol.29, No.2, pp. 303-316, 1991.
  10. [10] M. Wagner, J. Morehouse, and S. Melkote, “Prediction of Part Orientation Error Tolerance of a Robotic Gripper,” Robotics and Computer-Integrated Manufacturing, Vol.25, No.2, pp. 449-459, 2009.
  11. [11] S. Ragunathan and L. Karunamoorthy, “Modular Reconfigurable Robotic Gripper for Limp Material Handling in Garment Industries,” Int. J. of Robotics and Automation 2008, Vol.23, No.6, pp. 213-219, 2008.
  12. [12] Y. Yokokohji, J. S. Martin, and M. Fujiwara, “Dynamic manipulability of multifingered grasping,” IEEE Trans. on Robotics, Vol.25, No.4, pp. 947-954, 2009.
  13. [13] E. Brown, N. Rodenberg, J. Amend, A. Mozeika, E. Steltz, M. Zakin, H. Lipson, and H. Jaeger, “Universal Robotic Gripper Based on the Jamming of Granular Material,” Proc. of the National Academy of Sciences, Vol.107, No.44, pp. 18809-18814, 2010.
  14. [14] D. Lane, J. Davies, G. Robinson, D. O’Brien, J. Sneddon, E. Seaton, and A. Elfstrom, “The AMADEUS dextrous subsea hand: design, modeling, and sensor processing,” IEEE J. of Oceanic Engineering, Vol.24, No.1, pp. 96-111, 1999.
  15. [15] D. Roy, “Estimation of Grip Force and Slip Behavior During Robotic Grasp Using Data Fusion and Hypothesis Testing: Case Study with a Matrix Sensor,” J. of Intelligent and Robotic Systems, Vol.50, No.1, pp. 41-71, 2007.
  16. [16] K. S. M. Sahari, H. Seki, Y. Kamiya, and M. Hikizu, “Passive Edge Tracing of Deformable Object by Robot,” J. of Robotics and Mechatronics, Vol.23, No.3, pp. 458-461, 2011.
  17. [17] H. Sugiuchi, S. Watanabe, Y. Hasegawa, and M. Nornoto, “A control system for multi-fingered robotic hand with distributed touch sensor,” In Industrial Electronics Society 2000 (IECON 2000), 26th Annual Conf. of the IEEE, Vol.1, pp. 434-439, IEEE, 2000.
  18. [18] D. Sun, C. Willingham, A. Durrani, P. King, K. Cleary, and B. Wood, “A Novel End-Effector Design for Robotics in Image Guided Needle Procedures,” The Int. J. of medical robotics computer assisted surgery: MRCAS, Vol.2, No.1, pp. 91-97, 2006.
  19. [19] H. Tanaka, T. Tomizawa, Y. Sumi, J. H. Lee, H. M. Do, B. K. Kim, T. Tanikawa, H. Onda, and K. Ohba, “Visual Marker System for Autonomous Object Handling by Assistive Robotic Arm,” J. of Robotics and Mechatronics, Vol.23, No.4, 2011.
  20. [20] A. Dollar and R. Howe, “A robust compliant grasper via shape deposition manufacturing,” IEEE/ASME Trans. on Mechatronics, Vol.11, No.2, pp. 154-161, 2006.
  21. [21] R. Kolluru, K. Valavanis, S. Smith, and N. Tsourveloudis, “Design fundamentals of a reconfigurable robotic gripper system,” IEEE Trans. on Systems, Man and Cybernetics, Part A: Systems and Humans, Vol.30, No.2, pp. 181-187, 2000.
  22. [22] G. Monkman, S. Hesse, and R. Steinmann, “Robot Grippers,” Vch Verlagsgesellschaft Mbh, 2007.
  23. [23] W. Townsend, “The Barrett Hand Grasper–Programmably Flexible Part Handling and Assembly,” Industrial Robot: an Int. J., Vol.27, No.3, pp. 181-188, 2000.
  24. [24] J. Huang, P. Di, T. Fukuda, and T. Matsuno, “Robust Model-Based Online Fault Detection forMating Process of Electric Connectors in Robotic Wiring Harness Assembly Systems,” IEEE Trans. on Control Systems Technology, Vol.18, No.5, pp. 1207-1215, 2010.
  25. [25] J. Huang, T. Fukuda, and T. Matsuno, “Model-based Intelligent Fault Detection and Diagnosis for Mating Electric Connectors in Robotic Wiring Harness Assembly Systems,” IEEE/ASME Trans. on Mechatronics, Vol.13, No.1, pp. 86-94, 2008.

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