Reduced-order modeling of soft robots

Chenevier, J. ; Gonzalez, D. (Universidad de Zaragoza) ; Aguado, J.V. ; Chinesta, F. ; Cueto, E. (Universidad de Zaragoza)
Reduced-order modeling of soft robots
Resumen: We present a general strategy for the modeling and simulation-based control of soft robots. Although the presented methodology is completely general, we restrict ourselves to the analysis of a model robot made of hyperelastic materials and actuated by cables or tendons. To comply with the stringent real-time constraints imposed by control algorithms, a reduced-order modeling strategy is proposed that allows to minimize the amount of online CPU cost. Instead, an offline training procedure is proposed that allows to determine a sort of response surface that characterizes the response of the robot. Contrarily to existing strategies, the proposed methodology allows for a fully non-linear modeling of the soft material in a hyperelastic setting as well as a fully non-linear kinematic description of the movement without any restriction nor simplifying assumption. Examples of different configurations of the robot were analyzed that show the appeal of the method.
Idioma: Inglés
DOI: 10.1371/journal.pone.0192052
Año: 2018
Publicado en: PloS one 13, 2 (2018), e0192052[15 pp]
ISSN: 1932-6203

Factor impacto JCR: 2.776 (2018)
Categ. JCR: MULTIDISCIPLINARY SCIENCES rank: 23 / 69 = 0.333 (2018) - Q2 - T2
Factor impacto SCIMAGO: 1.1 - Agricultural and Biological Sciences (miscellaneous) (Q1) - Medicine (miscellaneous) (Q1) - Biochemistry, Genetics and Molecular Biology (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/CICYT/DPI2014-51844-C2-1-R
Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2015-72365-EXP
Tipo y forma: Article (Published version)
Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)

Creative Commons You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.


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 Record created 2018-04-13, last modified 2019-12-12


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