Davy, J orcid.org/0000-0001-9483-111X, Lloyd, P, Chandler, JH orcid.org/0000-0001-9232-4966 et al. (1 more author) (2023) A Framework for Simulation of Magnetic Soft Robots using the Material Point Method. IEEE Robotics and Automation Letters, 8 (6). pp. 3470-3477. ISSN 2377-3766
Abstract
Simulation represents a key aspect in the development of robot systems. The ability to simulate behavior of real-world robots provides an environment where robot designs can be developed and control systems optimized. Due to the use of external magnetic fields for actuation, magnetic soft robots can be wirelessly controlled and are easily miniaturized. However, the relationship between magnetic soft materials and external sources of magnetic fields present significant complexities in modelling due to the relationship between material elasticity and magnetic wrench (forces and torques). In this work, we present a simulation framework for magnetic soft robots using the Material Point Method (MPM) which integrates hyper-elastic material models with the magnetic wrench induced under external fields. Compared to existing Finite Element Methods (FEM), the presented MPM based framework inherently models self-collision between areas of the model and can capture the effect of forces in non-homogeneous magnetic fields. We demonstrate the ability of the MPM framework to model the influence of magnetic wrench on magnetic soft robots, capture dynamic behavior of robots under time-varying magnetic fields, and provide an accurate representation of deformation when colliding with obstacles. We show the versatility of MPM framework by comparing simulations to a range of real-world magnetic soft robot designs previously presented in the literature.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This is an author produced version of an article published in IEEE Robotics and Automation Letters, made available under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Modeling, control, and learning for soft robots, soft robot materials and design, simulation and animation |
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) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Apr 2023 13:20 |
Last Modified: | 15 Jun 2023 01:41 |
Published Version: | http://dx.doi.org/10.1109/lra.2023.3268016 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/lra.2023.3268016 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:198429 |