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Bilateral teleoperation with adaptive impedance control for contact tasks

Abstract : This paper presents an adaptive impedance control architecture for robotic teleoperation of contact tasks featuring continuous interaction with the environment. We use Learning from Demonstration (LfD) as a framework to learn variable stiffness control policies. Then, the learnt state-varying stiffness is used to command the remote manipulator, so as to adapt its interaction with the environment based on the sensed forces. Our system only relies on the on-board torque sensors of a commercial robotic manipulator and it does not require any additional hardware or user input for the estimation of the required stiffness. We also provide a passivity analysis of our system, where the concept of energy tanks is used to guarantee a stable behavior. Finally, the system is evaluated in a representative teleoperated cutting application. Results show that the proposed variablestiffness approach outperforms two standard constant-stiffness approaches in terms of safety and robot tracking performance.
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Contributor : Claudio Pacchierotti <>
Submitted on : Sunday, March 7, 2021 - 7:29:10 PM
Last modification on : Friday, March 19, 2021 - 11:00:10 AM



Youssef Michel, Rahaf Rahal, Claudio Pacchierotti, Paolo Robuffo Giordano, Dongheui Lee. Bilateral teleoperation with adaptive impedance control for contact tasks. IEEE Robotics and Automation Letters, IEEE 2021, pp.1-8. ⟨10.1109/LRA.2021.3066974⟩. ⟨hal-03161641⟩



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