An Advanced Compliance Controller for a Robot Manipulator Contacting with Unknown Environments

Dong Hyuk Cha; Myung Jin Chung; Jae Hong Shim

doi:10.4028/www.scientific.net/AMM.446-447.1266

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 446-447An Advanced Compliance Controller for a Robot...

An Advanced Compliance Controller for a Robot Manipulator Contacting with Unknown Environments

Abstract:

This paper proposes a novel design method of the compliance controller for robot manipulators. The neurofuzzy compliance controller (NFCC) proposed herein is an algorithm designed to automatically determine the suitable compliance for a given task or environment. The scheme dose not require any priori knowledge on a robot manipulator dynamics, a manipulator controller and an environment, and thus, it can be easily applied to the control of any robot manipulator systems. Through a series of experiments, effectiveness of the algorithm has been verified.

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Periodical:

Applied Mechanics and Materials (Volumes 446-447)

Pages:

1266-1270

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.446-447.1266

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Online since:

November 2013

Authors:

Dong Hyuk Cha*, Myung Jin Chung, Jae Hong Shim

Keywords:

Compliance Control, Neurofuzzy, Robot Manipulator

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* - Corresponding Author

References

[1] N. Hogan, Impedance control: an approach to manipulation, ASME J. Dynamic System, Meas. and Control, Vol. 107 (1985), pp.1-24.

Google Scholar

[2] W. S. Kim, Shared compliant control: A stability analysis and experiments, Proc. IEEE Int. Conf. Robotics and Automation, (1990), pp.620-623.

Google Scholar

[3] B. Waibel, and H. Kazerooni, Theory and experiments on the stability of robot compliance control, IEEE Trans. Robotics and Automation, Vol. 7, No. 1 (1991), pp.95-104.

DOI: 10.1109/70.68073

Google Scholar

[4] D. H. Cha and H. S. Cho, A neurofuzzy model-based compliance controller with application to a telerobot system, Control Engineering Practice, Vol. 4, No. 3 (1996), pp.319-330.

DOI: 10.1016/0967-0661(96)00008-1

Google Scholar

[5] V. Vitiello, and S. Lee, Emerging Robotic Platforms for Minimally Invasive Surgery, IEEE Reviews in Biomedical Engineering. Vol. 6 (2013), pp.111-126.

DOI: 10.1109/rbme.2012.2236311

Google Scholar

[6] A. G. Barto, etc., Neuronlike adaptive elements that can solve difficult learning control problems, IEEE Trans. Systems, Man and Cybernetics, Vol. 13, No. 5 (1983), pp.834-846.

DOI: 10.1109/tsmc.1983.6313077

Google Scholar

[7] C. C. Lee, A self-learning rule-based controller with approximate reasoning and neural nets", Proc. IFAC , 90 World Congress, Vol. 7, (1990), pp.59-64.

Google Scholar