Da Veiga, T, Chandler, JH orcid.org/0000-0001-9232-4966, Pittiglio, G et al. (5 more authors) (2021) Material Characterization for Magnetic Soft Robots. In: 2021 IEEE 4th International Conference on Soft Robotics (RoboSoft). 2021 IEEE 4th International Conference on Soft Robotics (RoboSoft), 12-16 Apr 2021, New Haven, CT, USA. IEEE , pp. 335-342. ISBN 978-1-7281-7714-4
Abstract
Magnetic soft robots are increasingly popular as they provide many advantages such as miniaturization and tetherless control that are ideal for applications inside the human body or in previously inaccessible locations.While non-magnetic elastomers have been extensively characterized and modelled for optimizing the fabrication of soft robots, a systematic material characterization of their magnetic counterparts is still missing. In this paper, commonly employed magnetic materials made out of Ecoflex™ 00-30 and Dragon Skin™ 10 with different concentrations of NdFeB microparticles were mechanically and magnetically characterized. The magnetic materials were evaluated under uniaxial tensile testing and their behavior analyzed through linear and hyperelastic model comparison. To determine the corresponding magnetic properties, we present a method to determine the magnetization vector, and magnetic remanence, by means of a force and torque load cell and large reference permanent magnet; demonstrating a high level of accuracy. Furthermore, we study the influence of varied magnitude impulse magnetizing fields on the resultant magnetizations. In combination, by applying improved, material-specific mechanical and magnetic properties to a 2-segment discrete magnetic robot, we show the potential to reduce simulation errors from 8.5% to 5.4%.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Soft Robot Materials and Design , Modeling , Control , Learning for Soft Robots , Surgical Robotics , Steerable Catheters/Needles |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/R045291/1 EU - European Union 818045 EPSRC (Engineering and Physical Sciences Research Council) EP/V009818/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Jul 2021 13:05 |
Last Modified: | 28 Jul 2021 13:05 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/robosoft51838.2021.9479189 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:176469 |