Sensing Soft Robot Shape Using IMUs

An Experimental Investigation

Book Chapter (2021)
Author(s)

Josie Hughes (Massachusetts Institute of Technology)

F. Stella (TU Delft - Learning & Autonomous Control)

C. Lieu (TU Delft - Learning & Autonomous Control, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Technische Universität München)

Daniela Rus (Massachusetts Institute of Technology)

Research Group
Learning & Autonomous Control
Copyright
© 2021 Josie Hughes, F. Stella, C. Della Santina, Daniela Rus
DOI related publication
https://doi.org/10.1007/978-3-030-71151-1_48
More Info
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Publication Year
2021
Language
English
Copyright
© 2021 Josie Hughes, F. Stella, C. Della Santina, Daniela Rus
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
Pages (from-to)
543-552
ISBN (print)
978-3-030-71150-4
ISBN (electronic)
978-3-030-71151-1
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Shape estimation of soft robotic systems is challenging due to the range of deformations that can be achieved, and the limited availability of physically compatible sensors. We propose a method of reconstruction using Inertial Measurement Units (IMUs), which are mounted on segments of a deformable manipulator. This approach utilizes the piecewise constant curvature model in combination with the quaternion data from IMUs to allow for accuracy reconstruction and closed-loop control. A key strength of this approach is that it is hardware agnostic, and could be used on any soft structure to provide pose reconstruction and controllability. We explore this approach experimentally on a growing, extendable 3D printed continuum body structure, demonstrating that high accuracy reconstruction that can be achieved.

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