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Journal Articles PLoS ONE Year : 2018

Reduced-order modeling of soft robots


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. © 2018 Chenevier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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hal-01942890 , version 1 (03-12-2018)



Jean Chenevier, David Gonzalez, J. Vicente Aguado, Francisco Chinesta, Elias Cueto. Reduced-order modeling of soft robots. PLoS ONE, 2018, 13 (2), pp.e0192052. ⟨10.1371/journal.pone.0192052⟩. ⟨hal-01942890⟩
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