Learning Control And Computational Models Of Human Motor Systems

Grant number: DP130100849 | Funding period: 2013 - 2017

Completed

Abstract

With the aim of understanding how humans learn their body movements, this project addresses fundamental cross-disciplinary issues of learning control, robotics and computational models of human motor systems. The results will lead to improvements in smart industrial automation and the development of more effective rehabilitation stategies.

Related publications (5)

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Dual-loop iterative optimal control for the finite horizon LQR problem with unknown dynamics

Justin Fong, Ying Tan, Vincent Crocher, Denny Oetomo, Iven Mareels

2018-01-01

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Modeling of Endpoint Feedback Learning Implemented Through Point-to-Point Learning Control

Shou-Han Zhou, Ying Tan, Denny Oetomo, Chris Freeman, Etienne Burdet, Iven Mareels

2017-09-01

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Learning control in robot-assisted rehabilitation of motor skills–a review

SH Zhou, J Fong, V Crocher, Y Tan, D Oetomo, I Mareels

2016-01-02

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Effect of sensory experience on motor learning strategy

Shou-Han Zhou, Denny Oetomo, Ying Tan, Iven Mareels, Etienne Burdet

2015-02-15

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A Tool to Address Movement Quality Outcomes of Post-Stroke Patients

V CROCHER, J Fong, M Klaic, D Oetomo, Y Tan

2014-01-01

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