Simultaneous Learning of Robot Impedance Parameters Using Neural Networks

Mutsuhiro Terauchi; Yoshiyuki Tanaka; Seishiro Sakaguchi; Nan Bu; Toshio Tsuji

doi:10.20965/jrm.2007.p0106

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JRM Vol.19 No.1 pp. 106-113

doi: 10.20965/jrm.2007.p0106

(2007)

Paper:

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Simultaneous Learning of Robot Impedance Parameters Using Neural Networks

Mutsuhiro Terauchi^, Yoshiyuki Tanaka^,
Seishiro Sakaguchi^, Nan Bu^,
and Toshio Tsuji^

^*Faculty of Psychological Sciences, Hiroshima International University, 555-36 Kurose-Gakuendai, Higashi-Hiroshima, Hiroshima 724-0695, Japan

^**Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8527, Japan

^***National Institute of Advanced Industrial Science and Technology, 807-1 Shunku, Tosu, Saga 841-0052, Japan

Received:

June 6, 2006

Accepted:

July 31, 2006

Published:

February 20, 2007

Keywords:

robot manipulator, impedance control, neural networks, learning of impedance parameters

Abstract

Impedance control is one of the most effective control methods for interaction between a robotic manipulator and its environment. Robot impedance control regulates the response of the manipulator to contact and virtual impedance control regulates the manipulator's response before contact. Although these impedance parameters may be regulated using neural networks, conventional methods do not consider regulating robot impedance and virtual impedance simultaneously. This paper proposes a simultaneous learning method to regulate the impedance parameters using neural networks. The validity of the proposed method is demonstrated in computer simulations of tasks by a multi-joint robotic manipulator.

Cite this article as:

M. Terauchi, Y. Tanaka, S. Sakaguchi, N. Bu, and T. Tsuji, “Simultaneous Learning of Robot Impedance Parameters Using Neural Networks,” J. Robot. Mechatron., Vol.19 No.1, pp. 106-113, 2007.

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References

[1] N. Hogan, “Impedance Control: An Approach to Manipulation, Parts I, II, III,” ASME Journal of Dynamic Systems, Measurement, and Control, Vol.107, No.1, pp. 1-24, 1985.
[2] N. Hogan, “Stable Execution of contact tasks using impedance control,” Proc. IEEE International Conference on Robotics and Automation, pp. 1047-1054, 1987.
[3] T. Sakaki and S. Tachi, “Contact Stability Analysis on Some Impedance Control Methods,” Journal of the Robotics Society of Japan, Vol.12, No.3, pp. 155-162, 1994 (in Japanese).
[4] T. Sakaki and S. Tachi, “A Stabilizing Method of Contact Tasks on Servo-based Impedance Control,” Journal of the Robotics Society of Japan, Vol.13, No.5, pp. 77-83, 1995 (in Japanese).
[5] T. Tsuji and M. Kaneko, “Non-Contact Impedance Control for Redundant Manipulators,” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, Vol.29, No.2, pp. 184-193, March, 1999.
[6] T. Tsuji and M. Kaneko, “Non-contact Impedance Control for Redundant Manipulator,” IEEE Transaction on Systems, Man, and Cybernetics – PartA, Vol.29, No.2, pp. 184-193, 1999.
[7] Y. Nakabo and M. Ishikawa, “Visual Impedance Using 1ms Visual Feedback System,” In proceedings of the 1998 IEEE Int. Conf. Robotics and Automation, pp. 2333-2338, 1998.
[8] G. Gomi and M. Kawato, “Neural Network Control for a Closed Loop System Using Feedback-Error-Learning,” Neural Networks, Vol.6, No.7, pp. 933-946, 1993.
[9] S. Jung and T. C. Hsia, “On Neural Network Application to Robust Impedance Control of Robot Manipulators,” Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 869-974, 1995.
[10] T. Tsuji, M. Nishida, and K. Ito, “Iterative Learning of Impedance Parameters for Manipulator Control Using Neural Networks,” Transactions of the Society of Instrument and Control Engineers, Vol.28, No.12, pp. 1461-1468, 1992 (in Japanese).
[11] T. Tsuji, K. Ito, and P. Morasso, “Neural Network Learning of Robot Arm Impedance in Operational Space,” IEEE Transaction on Systems, Man, and Cybernetics – PartB, Vol.26, No.2, pp. 290-298, 1996.
[12] T. Tsuji and Y. Tanaka, “On-line Learning of Robot Arm Impedance Using Neural Networks,” Robotics and Autonomous Systems, Vol.52, No.4, pp. 257-271, 2005.
[13] T. Tsuji and Y. Tanaka, “On-line Learning of Robot Arm Impedance Using Neural Networks,” Robotics and Autonomous Systems, Vol.52, No.4, pp. 257-271, 2005.
[14] T. Tsuji, M. Terauchi, and Y. Takana, “On-line Learning of Virtual Impedance Parameters in Non-contact Impedance Control Using Neural Networks,” IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics (Technical correspondence), pp. 2112-2118, 2004.
[15] T. Yoshikawa, “Foundations of Robot Control,” Corona Publishing Co. LTD., 1988 (in Japanese).

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] N. Hogan, “Impedance Control: An Approach to Manipulation, Parts I, II, III,” ASME Journal of Dynamic Systems, Measurement, and Control, Vol.107, No.1, pp. 1-24, 1985.

[2] [2] N. Hogan, “Stable Execution of contact tasks using impedance control,” Proc. IEEE International Conference on Robotics and Automation, pp. 1047-1054, 1987.

[3] [3] T. Sakaki and S. Tachi, “Contact Stability Analysis on Some Impedance Control Methods,” Journal of the Robotics Society of Japan, Vol.12, No.3, pp. 155-162, 1994 (in Japanese).

[4] [4] T. Sakaki and S. Tachi, “A Stabilizing Method of Contact Tasks on Servo-based Impedance Control,” Journal of the Robotics Society of Japan, Vol.13, No.5, pp. 77-83, 1995 (in Japanese).

[5] [5] T. Tsuji and M. Kaneko, “Non-Contact Impedance Control for Redundant Manipulators,” IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans, Vol.29, No.2, pp. 184-193, March, 1999.

[6] [6] T. Tsuji and M. Kaneko, “Non-contact Impedance Control for Redundant Manipulator,” IEEE Transaction on Systems, Man, and Cybernetics – PartA, Vol.29, No.2, pp. 184-193, 1999.

[7] [7] Y. Nakabo and M. Ishikawa, “Visual Impedance Using 1ms Visual Feedback System,” In proceedings of the 1998 IEEE Int. Conf. Robotics and Automation, pp. 2333-2338, 1998.

[8] [8] G. Gomi and M. Kawato, “Neural Network Control for a Closed Loop System Using Feedback-Error-Learning,” Neural Networks, Vol.6, No.7, pp. 933-946, 1993.

[9] [9] S. Jung and T. C. Hsia, “On Neural Network Application to Robust Impedance Control of Robot Manipulators,” Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 869-974, 1995.

[10] [10] T. Tsuji, M. Nishida, and K. Ito, “Iterative Learning of Impedance Parameters for Manipulator Control Using Neural Networks,” Transactions of the Society of Instrument and Control Engineers, Vol.28, No.12, pp. 1461-1468, 1992 (in Japanese).

[11] [11] T. Tsuji, K. Ito, and P. Morasso, “Neural Network Learning of Robot Arm Impedance in Operational Space,” IEEE Transaction on Systems, Man, and Cybernetics – PartB, Vol.26, No.2, pp. 290-298, 1996.

[12] [12] T. Tsuji and Y. Tanaka, “On-line Learning of Robot Arm Impedance Using Neural Networks,” Robotics and Autonomous Systems, Vol.52, No.4, pp. 257-271, 2005.

[13] [13] T. Tsuji and Y. Tanaka, “On-line Learning of Robot Arm Impedance Using Neural Networks,” Robotics and Autonomous Systems, Vol.52, No.4, pp. 257-271, 2005.

[14] [14] T. Tsuji, M. Terauchi, and Y. Takana, “On-line Learning of Virtual Impedance Parameters in Non-contact Impedance Control Using Neural Networks,” IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics (Technical correspondence), pp. 2112-2118, 2004.

[15] [15] T. Yoshikawa, “Foundations of Robot Control,” Corona Publishing Co. LTD., 1988 (in Japanese).

Simultaneous Learning of Robot Impedance Parameters Using Neural Networks

Mutsuhiro Terauchi*, Yoshiyuki Tanaka**, Seishiro Sakaguchi**, Nan Bu***, and Toshio Tsuji**

Mutsuhiro Terauchi^, Yoshiyuki Tanaka^,
Seishiro Sakaguchi^, Nan Bu^,
and Toshio Tsuji^