System Identification and Control of Valkyrie through SVA--Based Regressor Computation
Abstract
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.
Additional Information
This research is supported by NASA grant NNX11AN06H, NSF grants CNS-0953823 and CNS-1136104, and NHARP award 00512-0184-2009.Attached Files
Submitted - 1608.02683.pdf
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Additional details
- Eprint ID
- 92607
- Resolver ID
- CaltechAUTHORS:20190201-160856010
- NNX11AN06H
- NASA
- CNS-0953823
- NSF
- CNS-1136104
- NSF
- 00512-0184-2009
- Norman Hackerman Advanced Research Program (NHARP)
- Created
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2019-02-04Created from EPrint's datestamp field
- Updated
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2023-06-02Created from EPrint's last_modified field