Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICCAS.2013.6704029
Title: Continuous critic learning for robot control in physical human-robot interaction
Authors: Wang, C.
Li, Y.
Ge, S.S. 
Tee, K.P.
Lee, T.H. 
Keywords: continuous critic learning
impedance adaptation
robot-environment interaction
Issue Date: 2013
Source: Wang, C.,Li, Y.,Ge, S.S.,Tee, K.P.,Lee, T.H. (2013). Continuous critic learning for robot control in physical human-robot interaction. International Conference on Control, Automation and Systems : 833-838. ScholarBank@NUS Repository. https://doi.org/10.1109/ICCAS.2013.6704029
Abstract: In this paper, optimal impedance adaptation is investigated for interaction control in constrained motion. The external environment is modeled as a linear system with parameter matrices completely unknown and continuous critic learning is adopted for interaction control. The desired impedance is obtained which leads to an optimal realization of the trajectory tracking and force regulation. As no particular system information is required in the whole process, the proposed interaction control provides a feasible solution to a large number of applications. The validity of the proposed method is verified through simulation studies. © 2013 IEEE.
Source Title: International Conference on Control, Automation and Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/83582
ISBN: 9788993215052
ISSN: 15987833
DOI: 10.1109/ICCAS.2013.6704029
Appears in Collections:Staff Publications

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