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...

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Bibliographic Details
Main Authors: Kaeli, Jeffrey W. (Author), Singh, Hanumant (Author), Leonard, John Joseph (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2015-06-30T15:50:11Z.
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Online Access:Get fulltext
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100 1 0 |a Kaeli, Jeffrey W.  |e author 
100 1 0 |a Massachusetts Institute of Technology. Department of Mechanical Engineering  |e contributor 
100 1 0 |a Leonard, John Joseph  |e contributor 
700 1 0 |a Singh, Hanumant  |e author 
700 1 0 |a Leonard, John Joseph  |e author 
245 0 0 |a Visual summaries for low-bandwidth semantic mapping with autonomous underwater vehicles 
260 |b Institute of Electrical and Electronics Engineers (IEEE),   |c 2015-06-30T15:50:11Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/97584 
520 |a 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. 
546 |a en_US 
655 7 |a Article 
773 |t Proceedings of the 2014 IEEE/OES Autonomous Underwater Vehicles (AUV) Conference