Hostname: page-component-89b8bd64d-9prln Total loading time: 0 Render date: 2026-05-08T04:21:42.419Z Has data issue: false hasContentIssue false
  • English
  • Français

Bayesian framework for bilateral teleoperation systems over unreliable network

Published online by Cambridge University Press:  08 April 2015

Jae-young Lee  and
Shahram Payandeh
Jae-young Lee*
Affiliation:
Experimental Robotics Laboratory, the School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia, V5A 4Y1 Canada
Shahram Payandeh
Affiliation:
Experimental Robotics Laboratory, the School of Engineering Science, Simon Fraser University, 8888 University Drive, Burnaby, British Columbia, V5A 4Y1 Canada
*
*Corresponding author. E-mail: jaeyl@etri.re.kr
Get access Rights & Permissions [Opens in a new window]

Summary

In this paper, we present a novel stochastic framework for network-based bilateral teleoperation systems. A Bayesian approach, which provides robust tracking performance in real-world applications, is proposed to estimate and predict the stochastic variables and compensate for the unreliable network conditions. Combining with a practical approach in transport and application layers of the Internet, this paper demonstrates a high performance and efficient prediction and estimation method for bilateral teleoperation system. Experimental results show that the proposed Bayesian approach estimates and predicts true position and force data over unreliable network conditions, and therefore, improves the performance of overall teleoperation systems.

Keywords

TeleoperationHaptic interfacesPose estimation and registrationControl of robotic systemsForce control

Information

Type
Articles
Information
Robotica , Volume 34 , Issue 9 , September 2016 , pp. 2071 - 2086
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

1. Slawinski, E., Mut, V., Salinas, L. and Garcia, S., “Teleoperation of a mobile robot with time-varying delay and force feedback,” Robotica 30 (1), 67–77 (2012).CrossRefGoogle Scholar
2. Son, H. I., Jung, H., Lee, D. Y., Cho, J. H. and Bulthoff, H. H., “A psychophysical evaluation of haptic controllers: Viscosity perception of soft environments,” Robotica 32 (1), 1–17 (2014).CrossRefGoogle Scholar
3. Mirfakhrai, T. and Payandeh, S., “On using delay prediction in controlling force reflecting teleoperation over the Internet,” Robotica 23 (6), 809–813 (2005).CrossRefGoogle Scholar
4. Paxson, V., “End-to-end Internet packet dynamics,” IEEE/ACM Trans. Netw. 7 (3), 277–292 (1999).CrossRefGoogle Scholar
5. Anderson, R. J. and Spong, M. W., “Bilateral control of teleoperators with time delay,” IEEE Trans. Autom. Control 34 (5), 494–501 (1989).CrossRefGoogle Scholar
6. Niemeyer, G. and Slotine, J. J. E., “Stable adaptive teleoperation,” IEEE J. Ocean. Eng. 16 (1), 152–162 (1991).CrossRefGoogle Scholar
7. Lee, D. J. and Spong, M. W., “Passive bilateral teleoperation with constant time delay,” IEEE Trans. Robot. 22 (2), 269–281 (2006).CrossRefGoogle Scholar
8. Hannaford, B. and Ryu, J.-H., “Time-domain passivity control of haptic interfaces,” IEEE Trans. Robot. Autom. 18, 1–10 (2002).CrossRefGoogle Scholar
9. Ryu, J.-H., Kwon, D.-S. and Hannaford, B., “Stable teleoperation with time-domain passivity control,” IEEE Trans. Robot. Autom. 20 (2), 365–373 (2004).CrossRefGoogle Scholar
10. Niemeyer, G. and Slotine, J. J. E., “Towards Force-Reflecting Teleoperation Over the Internet,” Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium (May 1998) pp. 1909–1915.Google Scholar
11. Berestesky, P., Chopra, N. and Spong, M. W., “Discrete Time Passivity in Bilateral Teleoperation over the Internet,” Proceedings of the IEEE International Conference on Robotics and Automation, New Orleans (Apr. 2004) pp. 4557–4564.CrossRefGoogle Scholar
12. Hu, L., Liu, X., Liu, G. and Xu, S., “Trajectory tracking compensation for teleoperation with time delays,” Robotica 29 (6), 863–871 (2011).CrossRefGoogle Scholar
13. Munir, S. and Book, W., “Internet-based teleoperation using wave variables with prediction,” IEEE/ASME Trans. Mechatronics 7 (2), 124–133 (2002).CrossRefGoogle Scholar
14. Lee, J.-y. and Payandeh, S., “Stability of Internet-Based Teleoperation Systems using Bayesian Predictions,” Proceedings of the IEEE World Haptics, Istanbul, Turkey (Jun. 2011) pp. 499–503.Google Scholar
15. Slawinski, E. and Mut, V., “Control scheme including prediction and augmented reality for teleoperation of mobile robots,” Robotica 28 (1), 11–22 (2010).CrossRefGoogle Scholar
16. Uchimura, Y., Yakoh, T. and Ohnishi, K., “Bilateral robot system on the real-time network structure,” IEEE Trans. Ind. Electron. 51 (5), 940–946 (2004).CrossRefGoogle Scholar
17. Wirz, R., Marin, R., Ferre, M., Barrio, J., Claver, J. M. and Ortego, J., “Bidirectional transport protocol for teleoperated robots,” IEEE Trans. Ind. Electron. 56 (9), 3772–3781 (2009).CrossRefGoogle Scholar
18. Papoulis, A. and Pillai, S. U., Probability, Random Variables and Stochastic Processes (McGraw-Hill, New York, 2002).Google Scholar
19. Doucet, A., de Freitas, N. and Gordon, N., Sequential Monte Carlo Methods in Practice (Springer-Verlag, New York, 2001).CrossRefGoogle Scholar
20. Chen, Z., “Bayesian Filtering: From Kalman filters to particle filters, and beyond,” Adaptive Systems Lab, McMaster University, Hamilton, ON, Canada [Online]. Available at: http://soma.crl.mcmaster.ca/zhechen/download/ieee_bayesian.ps (2003).Google Scholar
21. Kwon, J., Choi, M., Park, F. C. and Chun, C., “Particle filtering on the Euclidean group: Framework and applications,” Robotica 25 (6), 725–737 (2007).CrossRefGoogle Scholar
22. Peralta-cabezas, J. I., Torres-torriti, M. and Guarini-hermann, M., “A comparison of Bayesian prediction technique for mobile robot trajectory tracking,” Robotica 26 (5), 571–585 (2008).CrossRefGoogle Scholar
23. Kurose, J. F. and Ross, K. W., Computer Networking: A Top-Down Approach (Pearson Education, Boston, MA, 2008).Google Scholar
24. Rodríguez-Seda, E. J., Lee, D. J. and Spong, M. W., “Experimental comparison study of control architectures for bilateral teleoperators,” IEEE Trans. Robot. 25 (6), 1304–1318 (2009).CrossRefGoogle Scholar
25. Lee, J.-y. and Payandeh, S., “Forward Error Correction for Reliable Teleoperation Systems Based on Haptic Data Digitization,” Proceedings of the IEEE International Conference on Robots and Systems (IROS), Tokyo, Japan (Nov. 2013) 5871–5877.Google Scholar