Imaging sonar-aided navigation for autonomous underwater harbor surveillance
In this paper we address the problem of drift-free navigation for underwater vehicles performing harbor surveillance and ship hull inspection. Maintaining accurate localization for the duration of a mission is important for a variety of tasks, such as planning the vehicle trajectory and ensuring cov...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2013
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| Online Access: | http://hdl.handle.net/1721.1/78636 https://orcid.org/0000-0002-2621-7633 |
| _version_ | 1826212963810279424 |
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| author | Johannsson, Hordur Kaess, Michael Englot, Brendan J. Hover, Franz S. Johnson, Leonard M. |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Johannsson, Hordur Kaess, Michael Englot, Brendan J. Hover, Franz S. Johnson, Leonard M. |
| author_sort | Johannsson, Hordur |
| collection | MIT |
| description | In this paper we address the problem of drift-free navigation for underwater vehicles performing harbor surveillance and ship hull inspection. Maintaining accurate localization for the duration of a mission is important for a variety of tasks, such as planning the vehicle trajectory and ensuring coverage of the area to be inspected. Our approach only uses onboard sensors in a simultaneous localization and mapping setting and removes the need for any external infrastructure like acoustic beacons. We extract dense features from a forward-looking imaging sonar and apply pair-wise registration between sonar frames. The registrations are combined with onboard velocity, attitude and acceleration sensors to obtain an improved estimate of the vehicle trajectory. We show results from several experiments that demonstrate drift-free navigation in various underwater environments. |
| first_indexed | 2024-09-23T15:40:56Z |
| format | Article |
| id | mit-1721.1/78636 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:40:56Z |
| publishDate | 2013 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/786362022-09-29T15:27:13Z Imaging sonar-aided navigation for autonomous underwater harbor surveillance Johannsson, Hordur Kaess, Michael Englot, Brendan J. Hover, Franz S. Johnson, Leonard M. Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Johannsson, Hordur Kaess, Michael Englot, Brendan J. Hover, Franz S. Johnson, Leonard M. In this paper we address the problem of drift-free navigation for underwater vehicles performing harbor surveillance and ship hull inspection. Maintaining accurate localization for the duration of a mission is important for a variety of tasks, such as planning the vehicle trajectory and ensuring coverage of the area to be inspected. Our approach only uses onboard sensors in a simultaneous localization and mapping setting and removes the need for any external infrastructure like acoustic beacons. We extract dense features from a forward-looking imaging sonar and apply pair-wise registration between sonar frames. The registrations are combined with onboard velocity, attitude and acceleration sensors to obtain an improved estimate of the vehicle trajectory. We show results from several experiments that demonstrate drift-free navigation in various underwater environments. United States. Office of Naval Research (Grant N00014-06-10043) 2013-04-29T20:16:05Z 2013-04-29T20:16:05Z 2010-10 Article http://purl.org/eprint/type/ConferencePaper 978-1-4244-6674-0 2153-0858 http://hdl.handle.net/1721.1/78636 Johannsson, H, M Kaess, B Englot, F Hover, and J Leonard. Imaging Sonar-aided Navigation for Autonomous Underwater Harbor Surveillance. In Pp. 4396–4403. 2010, IEEE. © Copyright 2010 IEEE https://orcid.org/0000-0002-2621-7633 en_US http://dx.doi.org/10.1109/IROS.2010.5650831 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2010 Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Institute of Electrical and Electronics Engineers (IEEE) IEEE |
| spellingShingle | Johannsson, Hordur Kaess, Michael Englot, Brendan J. Hover, Franz S. Johnson, Leonard M. Imaging sonar-aided navigation for autonomous underwater harbor surveillance |
| title | Imaging sonar-aided navigation for autonomous underwater harbor surveillance |
| title_full | Imaging sonar-aided navigation for autonomous underwater harbor surveillance |
| title_fullStr | Imaging sonar-aided navigation for autonomous underwater harbor surveillance |
| title_full_unstemmed | Imaging sonar-aided navigation for autonomous underwater harbor surveillance |
| title_short | Imaging sonar-aided navigation for autonomous underwater harbor surveillance |
| title_sort | imaging sonar aided navigation for autonomous underwater harbor surveillance |
| url | http://hdl.handle.net/1721.1/78636 https://orcid.org/0000-0002-2621-7633 |
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