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Joint Stiffness Identification from only Motor Force/Torque Data

Abstract : This paper deals with joint stiffness identification with only actual motor force/torque data instead of motor andload positions. The parameters are estimated by using the DIDIM method which needs only input data. This method was previously validated on a 6 DOF rigid robot and is now extended to flexible systems. The criterion to be minimized is the quadratic error between the measured actual motor force/torque and the simulated one. The optimal parameters are calculated with the Nelder Mead simplex algorithm. An experimental setup exhibits the experimental identification results and shows the effectiveness of our approach.
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https://hal.archives-ouvertes.fr/hal-00972556
Contributor : Ifsttar Cadic <>
Submitted on : Thursday, April 3, 2014 - 4:36:59 PM
Last modification on : Tuesday, September 21, 2021 - 4:12:11 PM

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  • HAL Id : hal-00972556, version 1

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Maxime Gautier, Alexandre Janot, A Jubien, Pierre Olivier Vandanjon. Joint Stiffness Identification from only Motor Force/Torque Data. 50th IEEE Conference on Decision and Control and European Control Conference, Dec 2011, France. pp 5088-5093. ⟨hal-00972556⟩

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