Lloyd, P, Hoshiar, AK, Da Veiga, T et al. (4 more authors) (2020) A learnt approach for the design of magnetically actuated shape forming soft tentacle robots. IEEE Robotics and Automation Letters, 5 (3). pp. 3937-3944. ISSN 2377-3766
Abstract
Soft continuum robots have the potential to revolutionize minimally invasive surgery. The challenges for such robots are ubiquitous; functioning within sensitive, unstructured and convoluted environments which are inconsistent between patients. As such, there exists an open design problem for robots of this genre. Research currently exists relating to the design considerations of on-board actuated soft robots such as fluid and tendon driven manipulators. Magnetically reactive robots, however, exhibit off-board actuation and consequently demonstrate far greater potential for miniaturization and dexterity. In this letter we present a soft, magnetically actuated, slender, shape forming ‘tentacle-like’ robot. To overcome the associated design challenges we also propose a novel design methodology based on a Neural Network trained using Finite Element Simulations. We demonstrate how our design approach generates static, two-dimensional tentacle profiles under homogeneous actuation based on predefined, desired deformations. To demonstrate our learnt approach, we fabricate and actuate candidate tentacles of 2 mm diameter and 42 mm length producing shape profiles within 8% mean absolute percentage error of desired shapes. With this proof of concept, we make the first step towards showing how tentacles with bespoke magnetic profiles may be designed and manufactured to suit specific anatomical constraints.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 IEEE. This is an author produced version of a paper accepted for publication in IEEE Robotics and Automation Letters. 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: | Modeling , control , and learning for soft robots , soft robot materials and design , 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 Royal Society wm150122 EPSRC (Engineering and Physical Sciences Research Council) EP/R045291/1 EU - European Union 818045 |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Mar 2020 13:16 |
Last Modified: | 01 May 2020 02:56 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers |
Identification Number: | 10.1109/LRA.2020.2983704 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158860 |