Jackson-Mills, G. orcid.org/0000-0003-4156-0955, Barber, A.R. orcid.org/0000-0002-3175-3510
, Andrew Blight et al. (3 more authors)
(Cover date: October 2022)
Non-Assembly 3D-Printed Walking Mechanism Utilising a Hexapod Gait.
Journal of Artificial Intelligence and Technology, 2 (4).
pp. 158-163.
ISSN 2766-8649
Abstract
Small inspection robots allow for the optimal exploration of environments and the collection of data from challenging areas, particularly where there may be small access points or tight and fragile surroundings. These robots can be custom-built for specific tasks, but the design and assembly process for this can be costly, both in resources and assembly time. The use of 3D printing to create Non-Assembly mechanisms can assist in saving time and resources by reducing the number of different components required and removing the necessity for complex assembly tasks. By iterating on previous work performed in the institute, this paper introduces a novel robot design to push the capabilities of Non-Assembly systems. By building on previous knowledge, this new walking robot improves on the previous iteration by creating a more robust and reliable system, more capable of effectively exploring challenging environments accurately, while still using practices designed to save on cost and production time. Benchmark tests were performed to provide an accurate comparison against the previous design and highlight the robots marked improvements in positional accuracy over its predecessor.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2022. This is an open access article published under the CC BY license (https://creativecommons.org/licenses/by/4.0/). |
Keywords: | robot, 3D printing, walking, hexapod |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) |
Funding Information: | Funder Grant number EPSRC (Engineering and Physical Sciences Research Council) EP/S016813/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Aug 2023 15:01 |
Last Modified: | 25 Aug 2023 15:01 |
Published Version: | https://ojs.istp-press.com/jait/article/view/112 |
Status: | Published |
Publisher: | Intelligence Science and Technology Press Inc. |
Identification Number: | 10.37965/jait.2022.0112 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:202451 |
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