Watson, M.T., Gladwin, D.T. orcid.org/0000-0001-7195-5435, Prescott, T.J. orcid.org/0000-0003-4927-5390 et al. (1 more author) (2018) Design and control of a novel omnidirectional dynamically balancing platform for remote inspection of confined and cluttered environments. In: 2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES). International Conference on Industrial Electronics for Sustainable Energy Systems, 31 Jan - 02 Feb 2018, Hamilton, New Zealand. IEEE , pp. 473-478. ISBN 978-1-5090-4974-5
Abstract
Remote inspection is a long standing field of interest for robotics researchers, in which robots are used to undertake inspection tasks in environments too hazardous or inaccessible to be directly entered by a human. Recent advances in gridscale battery storage have created a new set of unique hazardous indoor spaces with characteristics unsuitable for the deployment of existing teleoperated inspection robots. This paper outlines the problems encountered in these new environments, analyses existing approaches to robotic platform design, and proposes a better suited novel platform design, based on a dynamically balancing arrangement of Mecanum wheels. Its inverse kinematic and dynamics models are developed, a proof of concept prototype is constructed, and a constrained predictive controller is derived from the developed model. Experimental results demonstrate the efficacy of this new concept.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, 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 components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy. |
Keywords: | Wheels; Mobile robots; Inspection; Kinematics; Mathematical model; Predictive models |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 26 Jun 2018 10:09 |
Last Modified: | 25 Jul 2018 08:17 |
Published Version: | https://doi.org/10.1109/IESES.2018.8349923 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/IESES.2018.8349923 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:132164 |