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Motion optimization and parameter identification for a human and lower-back exoskeleton model

Manns, Paul ; Sreenivasa, Manish ; Millard, Matthew ; Mombaur, Katja

In: IEEE ROBOTICS AND AUTOMATION LETTERS, 2 (1 March 2017), Nr. 3. pp. 1564-1570. ISSN 2377-3766

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Abstract

Designing an exoskeleton to reduce the risk of low-back injury during lifting is challenging. Computational models of the human-robot system coupled with predictive movement simulations can help to simplify this design process. Here, we present a study that models the interaction between a human model actuated by muscles and a lower-back exoskeleton. We provide a computational framework for identifying the spring parameters of the exoskeleton using an optimal control approach and forward-dynamics simulations. This is applied to generate dynamically consistent bending and lifting movements in the sagittal plane. Our computations are able to predict motions and forces of the human and exoskeleton that are within the torque limits of a subject. The identified exoskeleton could also yield a considerable reduction of the peak lower-back torques as well as the cumulative lower-back load during the movements. This work is relevant to the research communities working on human-robot interaction, and can be used as a basis for a better human-centered design process.

Item Type: Article
Journal or Publication Title: IEEE ROBOTICS AND AUTOMATION LETTERS
Volume: 2
Number: 3
Date Deposited: 04 Apr 2017 11:56
Date: 1 March 2017
ISSN: 2377-3766
Page Range: pp. 1564-1570
Faculties / Institutes: The Faculty of Mathematics and Computer Science > Department of Computer Science
Subjects: 500 Natural sciences and mathematics
600 Technology (Applied sciences)
610 Medical sciences Medicine
Controlled Keywords: robotics, exoskeleton, optimal control
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