Presentation + Paper
18 May 2017 Toward experimental validation of a model for human sensorimotor learning and control in teleoperation
Eatai Roth, Darrin Howell, Cydney Beckwith, Samuel A. Burden
Author Affiliations +
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.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eatai Roth, Darrin Howell, Cydney Beckwith, and Samuel A. Burden "Toward experimental validation of a model for human sensorimotor learning and control in teleoperation", Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 101941X (18 May 2017); https://doi.org/10.1117/12.2263844
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Systems modeling

Feedback control

Nonlinear dynamics

Control systems

Performance modeling

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