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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
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Summary

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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 

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