Parrott, C., Dodd, T.J., Boxall, J. et al. (1 more author) (2020) Simulation of the behavior of biologically-inspired swarm robots for the autonomous inspection of buried pipes. Tunnelling and Underground Space Technology, 101. 103356. ISSN 0886-7798
Abstract
The use of robots for the inspection of buried pipelines has gained popularity over the past decade. In this paper we move the vision forward by examining what behavior and attributes would be required for these robots to become autonomous and pervasive within buried water pipe infrastructure. We present the results from novel simulations to evidence the inspection capability of autonomous robots, investigating operation, cooperation and communication attributes. The simulation uses a biologically-inspired behavior that provides complete and consistent coverage of real life example clean water distribution management areas. We show that autonomous robots could operate without a centralized controller and benefit from having some degree of in-pipe communication. We evidence the ability to adapt to changes in communication, speed, and flow conditions. The mathematical model that we derive through the simulation is scalable with the change of network length, topology, robots’ speed and number. This work paves the way and sets the specifications for practical development of autonomous pervasive robots for the inspection of complex pipe networks.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier Ltd. This is an author produced version of a paper subsequently published in Tunnelling and Underground Space Technology. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Swarms; Robotics; Autonomy; Inspection; Stigmergy; Infrastructure |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 28 Apr 2020 15:12 |
Last Modified: | 27 Apr 2021 00:38 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.tust.2020.103356 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:159998 |