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System Identification and Control of Valkyrie through SVA--Based Regressor Computation

Kolathaya, Shishir and Morris, Benjamin J. and Sinnet, Ryan W. and Ames, Aaron D. (2016) System Identification and Control of Valkyrie through SVA--Based Regressor Computation. . (Unpublished)

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This paper demonstrates simultaneous identification and control of the humanoid robot, Valkyrie, utilizing Spatial Vector Algebra (SVA). In particular, the inertia, Coriolis-centrifugal and gravity terms for the dynamics of a robot are computed using spatial inertia tensors. With the assumption that the link lengths or the distance between the joint axes are accurately known, it will be shown that inertial properties of a robot can be directly evaluated from the inertia tensor. An algorithm is proposed to evaluate the regressor, yielding a run time of O(n^2). The efficiency of this algorithm yields a means for online system identification via the SVA--based regressor and, as a byproduct, a method for accurate model-based control. Experimental validation of the proposed method is provided through its implementation in three case studies: offline identification of a double pendulum and a 4-DOF robotic leg, and online identification and control of a 4-DOF robotic arm.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper
Kolathaya, Shishir0000-0001-8689-2318
Ames, Aaron D.0000-0003-0848-3177
Additional Information:This research is supported by NASA grant NNX11AN06H, NSF grants CNS-0953823 and CNS-1136104, and NHARP award 00512-0184-2009.
Funding AgencyGrant Number
Norman Hackerman Advanced Research Program (NHARP)00512-0184-2009
Record Number:CaltechAUTHORS:20190201-160856010
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92607
Deposited By: George Porter
Deposited On:04 Feb 2019 15:50
Last Modified:03 Oct 2019 20:46

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