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Nonlinear bilateral teleoperation using extended active observer for force estimation and disturbance suppression

Published online by Cambridge University Press:  29 January 2014

Linping Chan ,
Fazel Naghdy ,
David Stirling  and
Matthew Field
Linping Chan*
Affiliation:
School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
Fazel Naghdy
Affiliation:
School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
David Stirling
Affiliation:
School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
Matthew Field
Affiliation:
School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, Wollongong, NSW 2522, Australia
*
*Corresponding author. E-mail: lc842@uowmail.edu.au
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Summary

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A novel nonlinear teleoperation algorithm for simultaneous inertial parameters and force estimation at the master and slave sides of the teleoperation system is proposed. The scheme, called Extended Active Observer (EAOB), is an extension of the existing active observer. It provides effective force tracking at the master side with accurate position tracking at the slave side in the presence of inertial parameter variation and measurement noise. The proposed method only requires the measurement of robot position, and as a result significantly reduces the difficulty and cost of implementing bilateral teleoperation systems. The approach is described and its stability is analytically verified. The performance of the method is validated through computer simulation and compared with the Nicosia observer-based controller. According to the results, EAOB outperforms the Nicosia observer method and effectively rejects noise.

Keywords

TeleoperationAdaptive controlExtended active observerForce estimationDisturbance rejection

Information

Type
Articles
Information
Robotica , Volume 33 , Issue 1 , January 2015 , pp. 61 - 86
Copyright
Copyright © Cambridge University Press 2014 

References

1.Lawrence, D. A., “Stability and transparency in bilateral teleoperation,” IEEE Trans. Robot. Autom. 9 (5), 624–637 (1993).CrossRefGoogle Scholar
2.Tavakoli, M., Aziminejad, A., Patel, R. V. and Moallem, M., “Enhanced Transparency in Haptics-Based Master-Slave Systems,” American Control Conference, New York (2007) pp. 1455–1460.Google Scholar
3.Chen, W. H., Ballance, D. J., Gawthrop, P. J. and O'Reilly, J., “A nonlinear disturbance observer for robotic manipulators,” IEEE Trans. Ind. Electron. 47 (4), 932–938 (2000).CrossRefGoogle Scholar
4.Daly, J. M. and Wang, D. W. L., “Bilateral Teleoperation Using Unknown Input Observers for Force Estimation,” American Control Conference, St. Louis, MO (2009) pp. 89–95.Google Scholar
5.Ahn, H. S., “Synchronization of Bilateral Teleoperation Systems Using State and Force Observer,” International Conference on Control, Automation and Systems, Gyeonggi-do, Korea (2010) pp. 1362–1365.Google Scholar
6.Nicosia, S. and Tomei, P., “Robot control by using only joint position measurements,” IEEE Trans. Autom. Control 35 (9), 1058–1061 (1990).CrossRefGoogle Scholar
7.Gourdeau, R. and Schwartz, H. M., “Adaptive control of robotic manipulators using an extended Kalman filter,” J. Dyn. Syst. Meas. Control 115 (1), 203–208 (1993).CrossRefGoogle Scholar
8.Rosen, J., Hannaford, B., MacFarlane, M. and Sinanan, M., “Force controlled and teleoperated endoscopic grasper for minimally invasive surgery-experimental performance evaluation,” IEEE Trans. Biomed. Eng. 46 (10), 1212–1221 (1999).CrossRefGoogle ScholarPubMed
9.Ni, L. and Wang, D. W. L., “A gain-switching control scheme for position-error-based bilateral teleoperation: Contact stability analysis and controller design,” Int. J. Robot. Res. 23 (3), 255–274 (2004).CrossRefGoogle Scholar
10.Lawrence, D. A., “Stability and transparency in bilateral teleoperation,” IEEE Trans. Robot. Autom. 9 (5), 624–637 (1993).CrossRefGoogle Scholar
11.Cortesão, R., “On Kalman active observers,” J. Intell. Robot Syst. 48 (2), 131–155 (2007).CrossRefGoogle Scholar
12.Cortesão, R., Koeppe, R., Nunes, U. and Hirzinger, G., “Data fusion for robotic assembly tasks based on human skills,” IEEE Trans. Robot. 20 (6), 941–952 (2004).CrossRefGoogle Scholar
13.Richard, G., “Adaptive Control of Robotic Manipulators,” Ph.D. Thesis, Carleton University, Ottawa, ON, Canada (1990).Google Scholar
14.Kalman, R. E. and Bucy, R. S., “New results in linear filtering and prediction theory,” ASME J. Basic Eng. 83 (1), 95–108 (1961).CrossRefGoogle Scholar
15.Sciavicco, L. and Siciliano, B., Modeling and Control of Robot Manipulators (McGraw-Hill, New York, NY, 1996).Google Scholar
16.Hokayem, P. F., and Spong, M. W., “Bilateral teleoperation: An historical survey,” Automatica 42 (12), 2035–2057 (2006).CrossRefGoogle Scholar