Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach
While underwater acoustic imaging devices are immune to issues such as turbidity and low visibility, the quality of information that an optical camera provides is richer, if they are in close proximity to an object of interest. Visual inspection is common for large underwater structures such as pipe...
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sg-ntu-dr.10356-1733942024-11-25T00:48:50Z Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach Azam, Abu Bakr Nguyen, Trung Kien Loke, Wesley Tosuni, Ardijan Tsanas, Aris Elhadidi, Basman Cai, Yiyu Interdisciplinary Graduate School (IGS) School of Mechanical and Aerospace Engineering Oceans 2024 - Singapore Energy Research Institute @ NTU (ERI@N) Engineering Kalman filter Image mosaic Forward-looking SONAR Underwater vehicle Visual inspection While underwater acoustic imaging devices are immune to issues such as turbidity and low visibility, the quality of information that an optical camera provides is richer, if they are in close proximity to an object of interest. Visual inspection is common for large underwater structures such as pipelines, where videos and image mosaics are prepared since individual images may not represent the structure. Current works focus on enhancing individual images and utilizing several techniques to determine features across the sequence of images to stitch them into a mosaic. Given the advances in non-visual sensor fusion for navigation, dependence of feature-based methods for mosaic generation can be avoided as challenging underwater environments may complicate feature extraction. Therefore, this study aims to generate image mosaics purely utilizing navigation information from a linear Kalman filter (KF), which fuses Inertial Measurement Unit (IMU) and SONAR data; a single-beam SONAR attached on an underwater vehicle (UWR) and forward looking SONAR (FLS) observing the UWR. From experiments, image mosaics were successfully prepared without the use of any feature-based methods, from a distance of 1 m from the target, with the mosaic being about 1.5 m in width, aided with navigational data from the KF. Submitted/Accepted version 2024-06-06T02:17:54Z 2024-06-06T02:17:54Z 2024 Conference Paper Azam, A. B., Nguyen, T. K., Loke, W., Tosuni, A., Tsanas, A., Elhadidi, B. & Cai, Y. (2024). Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach. Oceans 2024 - Singapore. https://dx.doi.org/10.1109/OCEANS51537.2024.10682265 https://hdl.handle.net/10356/173394 10.1109/OCEANS51537.2024.10682265 https://singapore24.oceansconference.org/ en © 2024 IEEE. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at http://doi.org/10.1109/OCEANS51537.2024.10682265. application/pdf |
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Engineering Kalman filter Image mosaic Forward-looking SONAR Underwater vehicle Visual inspection Azam, Abu Bakr Nguyen, Trung Kien Loke, Wesley Tosuni, Ardijan Tsanas, Aris Elhadidi, Basman Cai, Yiyu Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach |
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While underwater acoustic imaging devices are immune to issues such as turbidity and low visibility, the quality of information that an optical camera provides is richer, if they are in close proximity to an object of interest. Visual inspection is common for large underwater structures such as pipelines, where videos and image mosaics are prepared since individual images may not represent the structure. Current works focus on enhancing individual images and utilizing several techniques to determine features across the sequence of images to stitch them into a mosaic. Given the advances in non-visual sensor fusion for navigation, dependence of feature-based methods for mosaic generation can be avoided as challenging underwater environments may complicate feature extraction. Therefore, this study aims to generate image mosaics purely utilizing navigation information from a linear Kalman filter (KF), which fuses Inertial Measurement Unit (IMU) and SONAR data; a single-beam SONAR attached on an underwater vehicle (UWR) and forward looking SONAR (FLS) observing the UWR. From experiments, image mosaics were successfully prepared without the use of any feature-based methods, from a distance of 1 m from the target, with the mosaic being about 1.5 m in width, aided with navigational data from the KF. |
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Interdisciplinary Graduate School (IGS) |
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Interdisciplinary Graduate School (IGS) Azam, Abu Bakr Nguyen, Trung Kien Loke, Wesley Tosuni, Ardijan Tsanas, Aris Elhadidi, Basman Cai, Yiyu |
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Conference or Workshop Item |
author |
Azam, Abu Bakr Nguyen, Trung Kien Loke, Wesley Tosuni, Ardijan Tsanas, Aris Elhadidi, Basman Cai, Yiyu |
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Azam, Abu Bakr |
title |
Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach |
title_short |
Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach |
title_full |
Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach |
title_fullStr |
Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach |
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Acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach |
title_sort |
acoustic positioning enhanced optical image mosaics: a collaborative robot-assisted approach |
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2024 |
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https://hdl.handle.net/10356/173394 https://singapore24.oceansconference.org/ |
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