Piecewise Affine Curvature model

a Reduced-Order Model for Soft Robot-Environment Interaction Beyond PCC

Conference Paper (2023)
Author(s)

F. Stella (TU Delft - Learning & Autonomous Control, École Polytechnique Fédérale de Lausanne)

Qinghua Guan (Harbin Institute of Technology, École Polytechnique Fédérale de Lausanne)

C. Della Santina (Deutsches Zentrum für Luft- und Raumfahrt (DLR), TU Delft - Learning & Autonomous Control)

Josie Hughes (École Polytechnique Fédérale de Lausanne)

Research Group
Learning & Autonomous Control
Copyright
© 2023 F. Stella, Qinghua Guan, C. Della Santina, Josie Hughes
DOI related publication
https://doi.org/10.1109/RoboSoft55895.2023.10121939
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 F. Stella, Qinghua Guan, C. Della Santina, Josie Hughes
Research Group
Learning & Autonomous Control
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
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Abstract

Soft robot are celebrated for their propensity to enable compliant and complex robot-environment interactions. Soft robotic manipulators, or slender continuum structure robots have the potential to exploit these interactions to enable new exploration and manipulation capabilities and safe human-robot interactions. However, the interactions, or perturbations by external forces cause the soft structure to deform in an infinite degree of freedom (DOF) space. To control such system, reduced order models are needed; typically models consider piecewise sections of constant curvature although external forces often deform the structure out of the constant curvature hypothesis. In this work we perform an analysis of the trade-off between computational treatability and modelling accuracy. We then propose a new kinematic model, the Piecewise Affine Curvature (PAC) which we validate theoretically and experimentally showing that this higher-order model better captures the configuration of a soft continuum body robot when perturbed by the external forces. In comparison to the current state of the art Piecewise Constant Curvature (PCC) model we demonstrate up to 30% reduction in error for the end position of a soft continuum body robot.

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