Skip to main content
SpringerLink
Log in

Positioning in Releasing Manipulation by Iterative Learning Control

  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

In order to improve the positioning precision of the stop posture (position and orientation) of an object and decrease the trial numbers in our proposed releasing manipulation, two iterative learning control (ILC) schemes, learning control based on convergent condition (LCBCC), and learning control based on optimal principle (LCBOP) are designed in experimental-oriented way. These two methods are all based on a linearized system model. The experimental results show that these methods are effective. Having discussed the characteristics of these control methods, we conclude that in the case there is no enough system knowledge, LCBCC is the only choice to be used to learn the system knowledge; after the enough experience has been acquired, LCBOP is better than LCBCC, in the view of both of the convergent rate and the precision.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zhu, C., Aiyama, Y., Chawanya, T., Arai, T.: Releasing manipulation. Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and System, Osaka, Japan, pp. 911–916, 1996

  2. Zhu, C., Aiyama, Y., Arai, T.: The experimental characteristics of releasing manipulation. Proc. 3rd Asian Conf. on Robotics and its Application, Tokyo, Japan, pp. 911–916, 1997

  3. Zhu, C., Aiyama, Y., Arai, T.: Releasing manipulation with learning control. Proc. IEEE Int. Conf. on Robotics and Automation, Detroit, Michigan, USA, pp. 2793–2798, 1999

  4. Zhu, C., Aiyama, Y., Arai, T., Kawamura, A.: Frictional sliding motion in releasing manipulation. Adv. Robot. 19(2), 141–169 (2005)

    Article  Google Scholar 

  5. Zhu, C., Aiyama, Y., Arai, T., Kawamura, A.: Characteristics of frictional sliding motion in releasing manipulation. J. Robot. Mechatronics 18(1), 26–35 (2006)

    Google Scholar 

  6. Zhu, C., Aiyama, Y., Arai, T., Kawamura, A.: Characteristics analysis of frictional sliding motion. Journal of the Robotics Society of Japan 24(3), 140–151 (2006)

    Google Scholar 

  7. Huang, W.H., Krotkov, E.P., Mason, M.T.: Impulsive manipulation. Proc. IEEE Int. Conf. on Robotics and Automation, Nagoya, Aichi, Japan, pp. 120–125, 1995

  8. Huang, W.H., Mason, M.T.: Experiments in impulsive manipulation. Proc. IEEE Int. Conf. on Robotics and Automation, Leuven, Belgium, pp. 1077–1082, 1998

  9. Huang, W.H., Mason, M.T.: Mechanics, planning, and control for tapping. Int. J. Rob. Res. 19(20), 883–894 (October 2000)

    Article  Google Scholar 

  10. Partridge, C.B., Spong, M.W.: Control of planar rigid body sliding with impacts and friction. Int. J. Rob. Res. 336–348 (April, 2000)

  11. Spong, M.W.: Impact controllability of an air hockey puck. Syst. Control Lett. 42, 333–345 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  12. Arimoto, S., Kawamura, S., Miyazaki, F.: Bettering operation of robots by learning. J. Robot. Syst. 1, 123–140 (1984)

    Article  Google Scholar 

  13. Arimoto, S.: Learning control theory for robot motion. Int. J. Adapt. Control Signal Process. 4, 543–564 (1990)

    Article  MATH  Google Scholar 

  14. Togai, M., Yamano, O.: Analysis and design of an optimal learning control scheme for industrial robots: A discrete system approach. Proc. 24th IEEE Conf. on Decision and Control, Florida, pp. 1399–1404, (1985)

  15. Tayebi, A.: Robot visual serving with iterative learning control. Proc. the 2003 American Control Conference, Denver, CO, pp. 4518–4523, (2003)

  16. Norrlof, M.: An adaptive iterative learning control algorithm with experiments on an industrial robot. IEEE Trans. Robot. Autom. 18(2), 245–251 (2002)

    Article  Google Scholar 

  17. Bondi, P., Casalio, G., Gambardella, L.: On the iterative learning control theory for robotic manipulators. IEEE J. Robot. Autom. 4(1), 14–21 (February, 1988)

    Article  Google Scholar 

  18. Oh, S., Bien, Z., Suh, I.H.: An iterative learning control method with application for the robot manipulator. IEEE J. Robot. Autom. 4(5), 508–514 (October 1988)

    Article  Google Scholar 

  19. Goldsmith, W.: Impact: The Theory and Physical Behavior of Colliding Solids. Edward Arnold, London (1960)

    Google Scholar 

  20. Wang, Y., Mason, M.T.: Two-dimensional rigid-body collisions with friction. J. Appl. Mech. 59, 635–642 (Sept. 1992)

    Article  MATH  Google Scholar 

  21. Godwin, G.C., Sin, K.S.: Adaptive, Filtering, Prediction and Control. Prentice-Hall, Englewood, New Jersey (1984)

    Google Scholar 

  22. Press, W.H. et al.: Numerical Recipes in C: the art of Scientific Computing. 2nd edn. Cambridge University Press, Cambridge (1992)

Download references

Author information

Authors and Affiliations

  1. Department of Electrical & Computer, Yokohama National University, Engineering, 79-5 Tokiwadai, Hodogaya-ku, Yokohama, 240-8501, Japan

    Chi Zhu, Yasumichi Aiyama, Tamio Arai & Atsuo Kawamura

Authors
  1. Chi Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yasumichi Aiyama
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tamio Arai
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Atsuo Kawamura
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chi Zhu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhu, C., Aiyama, Y., Arai, T. et al. Positioning in Releasing Manipulation by Iterative Learning Control. J Intell Robot Syst 46, 383–404 (2006). https://doi.org/10.1007/s10846-006-9063-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-006-9063-3

Key words

Search

Navigation