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Autonomous control for miniaturized mobile robots in unknown pipe networks

Despite recent advances in robotic technology, sewer pipe inspection is still limited to conventional approaches that use cable-tethered robots. Such commercially available tethered robots lack autonomy, and their operation must be manually controlled via their tethered cables. Consequently, they ca...

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Autores principales: Nguyen, T. L., Blight, A., Pickering, A., Jackson-Mills, G., Barber, A. R., Boyle, J. H., Richardson, R., Dogar, M., Cohen, N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709324/
https://www.ncbi.nlm.nih.gov/pubmed/36466736
http://dx.doi.org/10.3389/frobt.2022.997415
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author Nguyen, T. L.
Blight, A.
Pickering, A.
Jackson-Mills, G.
Barber, A. R.
Boyle, J. H.
Richardson, R.
Dogar, M.
Cohen, N.
author_facet Nguyen, T. L.
Blight, A.
Pickering, A.
Jackson-Mills, G.
Barber, A. R.
Boyle, J. H.
Richardson, R.
Dogar, M.
Cohen, N.
author_sort Nguyen, T. L.
collection PubMed
description Despite recent advances in robotic technology, sewer pipe inspection is still limited to conventional approaches that use cable-tethered robots. Such commercially available tethered robots lack autonomy, and their operation must be manually controlled via their tethered cables. Consequently, they can only travel to a certain distance in pipe, cannot access small-diameter pipes, and their deployment incurs high costs for highly skilled operators. In this paper, we introduce a miniaturised mobile robot for pipe inspection. We present an autonomous control strategy for this robot that is effective, stable, and requires only low-computational resources. The robots used here can access pipes as small as 75 mm in diameter. Due to their small size, low carrying capacity, and limited battery supply, our robots can only carry simple sensors, a small processor, and miniature wheel-legs for locomotion. Yet, our control method is able to compensate for these limitations. We demonstrate fully autonomous robot mobility in a sewer pipe network, without any visual aid or power-hungry image processing. The control algorithm allows the robot to correctly recognise each local network configuration, and to make appropriate decisions accordingly. The control strategy was tested using the physical micro robot in a laboratory pipe network. In both simulation and experiment, the robot autonomously and exhaustively explored an unknown pipe network without missing any pipe section while avoiding obstacles. This is a significant advance towards fully autonomous inspection robot systems for sewer pipe networks.
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spelling pubmed-97093242022-12-01 Autonomous control for miniaturized mobile robots in unknown pipe networks Nguyen, T. L. Blight, A. Pickering, A. Jackson-Mills, G. Barber, A. R. Boyle, J. H. Richardson, R. Dogar, M. Cohen, N. Front Robot AI Robotics and AI Despite recent advances in robotic technology, sewer pipe inspection is still limited to conventional approaches that use cable-tethered robots. Such commercially available tethered robots lack autonomy, and their operation must be manually controlled via their tethered cables. Consequently, they can only travel to a certain distance in pipe, cannot access small-diameter pipes, and their deployment incurs high costs for highly skilled operators. In this paper, we introduce a miniaturised mobile robot for pipe inspection. We present an autonomous control strategy for this robot that is effective, stable, and requires only low-computational resources. The robots used here can access pipes as small as 75 mm in diameter. Due to their small size, low carrying capacity, and limited battery supply, our robots can only carry simple sensors, a small processor, and miniature wheel-legs for locomotion. Yet, our control method is able to compensate for these limitations. We demonstrate fully autonomous robot mobility in a sewer pipe network, without any visual aid or power-hungry image processing. The control algorithm allows the robot to correctly recognise each local network configuration, and to make appropriate decisions accordingly. The control strategy was tested using the physical micro robot in a laboratory pipe network. In both simulation and experiment, the robot autonomously and exhaustively explored an unknown pipe network without missing any pipe section while avoiding obstacles. This is a significant advance towards fully autonomous inspection robot systems for sewer pipe networks. Frontiers Media S.A. 2022-11-16 /pmc/articles/PMC9709324/ /pubmed/36466736 http://dx.doi.org/10.3389/frobt.2022.997415 Text en Copyright © 2022 Nguyen, Blight, Pickering, Jackson-Mills, Barber, Boyle, Richardson, Dogar and Cohen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Robotics and AI
Nguyen, T. L.
Blight, A.
Pickering, A.
Jackson-Mills, G.
Barber, A. R.
Boyle, J. H.
Richardson, R.
Dogar, M.
Cohen, N.
Autonomous control for miniaturized mobile robots in unknown pipe networks
title Autonomous control for miniaturized mobile robots in unknown pipe networks
title_full Autonomous control for miniaturized mobile robots in unknown pipe networks
title_fullStr Autonomous control for miniaturized mobile robots in unknown pipe networks
title_full_unstemmed Autonomous control for miniaturized mobile robots in unknown pipe networks
title_short Autonomous control for miniaturized mobile robots in unknown pipe networks
title_sort autonomous control for miniaturized mobile robots in unknown pipe networks
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9709324/
https://www.ncbi.nlm.nih.gov/pubmed/36466736
http://dx.doi.org/10.3389/frobt.2022.997415
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