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Proceedings Paper

Toward experimental validation of a model for human sensorimotor learning and control in teleoperation
Author(s): Eatai Roth; Darrin Howell; Cydney Beckwith; Samuel A. Burden
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Paper Abstract

Humans, interacting with cyber–physical systems (CPS), formulate beliefs about the system’s dynamics. It is natural to expect that human operators, tasked with teleoperation, use these beliefs to control the remote robot. For tracking tasks in the resulting human–cyber–physical system (HCPS), theory suggests that human operators can achieve exponential tracking (in stable systems) without state estimation provided they possess an accurate model of the system’s dynamics. This internalized inverse model, however, renders a portion of the system state unobservable to the human operator—the zero dynamics. Prior work shows humans can track through observable linear dynamics, thus we focus on nonlinear dynamics rendered unobservable through tracking control. We propose experiments to assess the human operator’s ability to learn and invert such models, and distinguish this behavior from that achieved by pure feedback control.

Paper Details

Date Published: 18 May 2017
PDF: 12 pages
Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101941X (18 May 2017); doi: 10.1117/12.2263844
Show Author Affiliations
Eatai Roth, Univ. of Washington (United States)
Darrin Howell, Univ. of Washington (United States)
Cydney Beckwith, Univ. of Washington (United States)
Samuel A. Burden, Univ. of Washington (United States)


Published in SPIE Proceedings Vol. 10194:
Micro- and Nanotechnology Sensors, Systems, and Applications IX
Thomas George; Achyut K. Dutta; M. Saif Islam, Editor(s)

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