Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles
A fundamental problem in autonomous underwater robotics is the high latency between the capture of image data and the time at which operators are able to gain a visual understanding of the survey environment. Typical missions can generate imagery at rates orders of magnitude greater than highly comp...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2015
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| Online Access: | http://hdl.handle.net/1721.1/97584 https://orcid.org/0000-0002-8863-6550 |
| _version_ | 1826191796241170432 |
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| author | Kaeli, Jeffrey W. Singh, Hanumant Leonard, John Joseph |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Kaeli, Jeffrey W. Singh, Hanumant Leonard, John Joseph |
| author_sort | Kaeli, Jeffrey W. |
| collection | MIT |
| description | A fundamental problem in autonomous underwater robotics is the high latency between the capture of image data and the time at which operators are able to gain a visual understanding of the survey environment. Typical missions can generate imagery at rates orders of magnitude greater than highly compressed images can be transmitted acoustically, delaying that understanding until after the robot has been recovered and the data analyzed. We present modifications to state-of-the-art online visual summary techniques that enable an autonomous robot to select representative images to be compressed and transmitted acoustically to the surface ship. These transmitted images then serve as the basis for a semantic map which, combined with scalar navigation data and classification masks, can provide an operator with a visual understanding of the survey environment while a mission is still underway. |
| first_indexed | 2024-09-23T09:01:26Z |
| format | Article |
| id | mit-1721.1/97584 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T09:01:26Z |
| publishDate | 2015 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/975842022-09-26T09:53:30Z Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles Kaeli, Jeffrey W. Singh, Hanumant Leonard, John Joseph Massachusetts Institute of Technology. Department of Mechanical Engineering Leonard, John Joseph A fundamental problem in autonomous underwater robotics is the high latency between the capture of image data and the time at which operators are able to gain a visual understanding of the survey environment. Typical missions can generate imagery at rates orders of magnitude greater than highly compressed images can be transmitted acoustically, delaying that understanding until after the robot has been recovered and the data analyzed. We present modifications to state-of-the-art online visual summary techniques that enable an autonomous robot to select representative images to be compressed and transmitted acoustically to the surface ship. These transmitted images then serve as the basis for a semantic map which, combined with scalar navigation data and classification masks, can provide an operator with a visual understanding of the survey environment while a mission is still underway. 2015-06-30T15:50:11Z 2015-06-30T15:50:11Z 2014-10 Article http://purl.org/eprint/type/ConferencePaper 978-1-4799-4344-9 978-1-4799-4345-6 http://hdl.handle.net/1721.1/97584 Kaeli, Jeffrey W., John J. Leonard, and Hanumant Singh. “Visual Summaries for Low-Bandwidth Semantic Mapping with Autonomous Underwater Vehicles.” 2014 IEEE/OES Autonomous Underwater Vehicles (AUV) (October 2014). https://orcid.org/0000-0002-8863-6550 en_US http://dx.doi.org/10.1109/AUV.2014.7054429 Proceedings of the 2014 IEEE/OES Autonomous Underwater Vehicles (AUV) Conference Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Other repository |
| spellingShingle | Kaeli, Jeffrey W. Singh, Hanumant Leonard, John Joseph Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles |
| title | Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles |
| title_full | Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles |
| title_fullStr | Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles |
| title_full_unstemmed | Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles |
| title_short | Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles |
| title_sort | visual summaries for low bandwidth semantic mapping with autonomous underwater vehicles |
| url | http://hdl.handle.net/1721.1/97584 https://orcid.org/0000-0002-8863-6550 |
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