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Robot mapping and localisation in metal water pipes using hydrophone induced vibration and map alignment by dynamic time warping

Ma, K., Schirru, M.M., Zahraee, A.H., Dwyer-Joyce, R., Boxall, J., DODD, Tony, Collins, R. and Anderson, S.R. (2017) Robot mapping and localisation in metal water pipes using hydrophone induced vibration and map alignment by dynamic time warping. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), May 29 - June 3, 2017. IEEE, pp. 2548-2553. ISBN 978-1-5090-4633-1

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Abstract or description

Water is a highly valuable resource so asset management of associated infrastructure is of critical importance. Water distribution pipe networks are usually buried, and so are difficult to access. Robots are therefore appealing for performing inspection and detecting damage to target repairs. However, robot mapping and localisation of buried water pipes has not been widely investigated to date, and is challenging because pipes tend to be relatively featureless. In this paper we propose a mapping and localisation algorithm for metal water pipes with two key novelties: the development of a new type of map based on hydrophone induced vibration signals of metal pipes, and a mapping algorithm based on spatial warping and averaging of dead reckoning signals used to calibrate the map (using dynamic time warping). Localisation is performed using both terrain-based extended Kalman filtering and also particle filtering. We successfully demonstrate and evaluate the approach on a combination of experimental and simulation data, showing improved localisation compared to dead reckoning.

Item Type: Book Chapter, Section or Conference Proceeding
Additional Information: © 2017 IEEE. This is an author produced version of a paper subsequently published in 2017 IEEE International Conference on Robotics and Automation (ICRA). Uploaded in accordance with the publisher's self-archiving policy.
Faculty: School of Creative Arts and Engineering > Engineering
Depositing User: Library STORE team
Date Deposited: 15 Jul 2020 14:53
Last Modified: 15 Jul 2020 14:53
URI: http://eprints.staffs.ac.uk/id/eprint/6236

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