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Stochastic estimation of human arm impedance using robots with nonlinear frictions: An experimental validation

Title
Stochastic estimation of human arm impedance using robots with nonlinear frictions: An experimental validation
Authors
Chang, Pyung HunPark, Kyung BinKang, Sang HoonKrebs, Hermano Igo GoHogan, Neville Catherine
Issue Date
2013
Citation
IEEE/ASME Transactions on Mechatronics, 18(2), 775-786
Type
Article
Article Type
Article
Keywords
ARM Impedance MeasurementConventional RobotsEstimationExperimental ValidationsExperimentsFrictionImpedance ControlImpedance MeasurementMultiple Coherence FunctionNon-Linear AnalysisProportional-Derivative ControlRobotic ArmsStochastic EstimationStochastic Estimation MethodsStochastic ModelsStochastic SystemsTribology
ISSN
1083-4435
Abstract
Inspired by previous research on the promising internal model-based impedance control (IMBIC) scheme, it was implemented and experiments were undertaken to determine the stochastic estimation of human arm impedance. A 2-DOF selective compliant assembly robot arm (SCARA) robot with significant nonlinear frictions was used in the experiments in order to test the accuracy and reliability of the estimation under nonlinear frictions, with the IMBIC and with a proportional derivative (PD) control, respectively. After the stochastic estimation method with the SCARA robot and the IMBIC was validated using a spring array, the method was applied to the estimation of human arm impedance. The experimental results demonstrated that the stochastic estimation using the IMBIC yields accurate and reliable estimations even under substantial frictions: the multiple coherence functions exceeded 0.95 throughout the frequency range investigated and the estimated magnitudes and phases matched well with a second-order best-fit model. Furthermore, the bestfit model demonstrated reasonable agreement with the results of previous research. The stochastic estimation using the IMBIC has also demonstrated effectiveness in the estimation of human arm impedance using conventional robots. © 2012 IEEE.
URI
http://hdl.handle.net/20.500.11750/5334
DOI
10.1109/TMECH.2012.2184767
Publisher
Institute of Electrical and Electronics Engineers
Files:
There are no files associated with this item.
Collection:
ETC1. Journal Articles


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