Impedance Learning for Robots Interacting with Unknown Environments

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Impedance Learning for Robots Interacting with Unknown Environments
Title:
Impedance Learning for Robots Interacting with Unknown Environments
Journal Title:
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
Publication Date:
04 November 2013
Citation:
Li, Y.; Ge, S.S., "Impedance Learning for Robots Interacting With Unknown Environments," Control Systems Technology, IEEE Transactions on , vol.PP, no.99, pp.1,1 doi: 10.1109/TCST.2013.2286194 keywords: {Adaptive control;Cost function;Force;Impedance;Position control;Robots;Trajectory;Adaptive control;impedance learning;interaction control;robotic control;unknown environment.}, URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6654275&isnumber=4389040
Abstract:
In this paper, impedance learning is investigated for robots interacting with unknown environments. A two-loop control framework is employed and adaptive control is developed for the inner-loop position control. The environments are described as time-varying systems with unknown parameters in the state-space form. The gradient-following scheme and betterment scheme are employed to obtain a desired impedance model, subject to unknown environments. The desired interaction performance is achieved in the sense that a defined cost function is minimized. Simulation and experiment studies are carried out to verify the validity of the proposed method.
License type:
PublisherCopyrights
Funding Info:
Description:
ISSN:
1063-6536
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