Worley, R. orcid.org/0000-0002-3607-2650 and Anderson, S. (2021) Robust efficient localization of robots in pipe networks using a particle filter for hybrid metric-topological space. In: Proceedings of 2021 European Conference on Mobile Robots (ECMR). 2021 European Conference on Mobile Robots (ECMR), 31 Aug - 03 Sep 2021, Bonn, Germany. IEEE (Institute of Electrical and Electronics Engineers) ISBN 9781665412148
Abstract
Water distribution and drainage pipe inspection and maintenance is costly, and could be improved by using robots to locate faults from within the pipes. Robot localization is critical in this operation, but is challenging due to the constraints of the pipe environment. An efficient, robust algorithm is needed for localization using limited sensors. A novel particle filter algorithm is proposed for localization, which estimates the robot’s position in a hybrid metric-topological state space, allowing efficient computation and relocalization. The algorithm is demonstrated in simulation at a large scale, considering substantial uncertainty in motion, measurements, and the map of the environment, showing an improvement over a benchmark algorithm developed for this application.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 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: | Location awareness; Uncertainty; Computational modeling; Robot sensing systems; Prediction algorithms; Extraterrestrial measurements; Particle filters |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number EPSRC Doctoral Training Partnership Scholarship N/A Engineering and Physical Sciences Research Council EP/S016813/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Sep 2021 11:23 |
Last Modified: | 20 Jan 2022 10:00 |
Status: | Published |
Publisher: | IEEE (Institute of Electrical and Electronics Engineers) |
Refereed: | Yes |
Identification Number: | 10.1109/ECMR50962.2021.9568829 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:177862 |