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|Title:||Continuous critic learning for robot control in physical human-robot interaction||Authors:||Wang, C.
|Keywords:||continuous critic learning
|Issue Date:||2013||Citation:||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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