Bhardwaj, H., Shaukat, N. orcid.org/0000-0002-8363-349X, Barber, A. orcid.org/0000-0002-3175-3510 et al. (8 more authors) (2025) Autonomous, Collaborative, and Confined Infrastructure Assessment with Purpose-Built Mega-Joey Robots. Robotics, 14 (6). 80. ISSN: 2218-6581
Abstract
The inspection of sewer pipes in the UK is costly, and if not inspected regularly, they are costly and disruptive to repair. This paper presents the Mega-Joey, a novel miniature, tether-less robot platform that is capable of autonomously navigating and assessing confined spaces, such as small-diameter underground pipelines. This paper also discusses a novel decentralized event-based-broadcasting autonomous exploration algorithm designed for exploring such pipe networks collaboratively. The designed robot is able to operate in pipes with an inclination of up to 20 degrees in dry and up to 10 degrees in wet conditions. A team of Mega-Joeys was used to explore a test network using the proposed algorithm. The experimental results show that the team of robots was able to explore a 3850 mm long test network within a faster period (36% faster) and in a more energy-efficient manner (approximately 54% more efficient) than a single robot could achieve.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2025 by the authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | wheeled robot; pipeline inspection; miniature; collaborative; autonomous; robotics teams |
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) |
Date Deposited: | 06 Oct 2025 13:23 |
Last Modified: | 06 Oct 2025 13:23 |
Status: | Published |
Publisher: | MDPI |
Identification Number: | 10.3390/robotics14060080 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:232477 |