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Autonomous underwater data muling using wireless optical communication and agile AUV control

Author(s)
Doniec, Marek Wojciech
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Alternative title
Autonomous underwater data muling using wireless optical communication and agile autonomous underwater vehicle control
Other Contributors
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Advisor
Daniela Rus.
Terms of use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582
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Abstract
Underwater exploration and surveillance currently relies on subsea cables and tethers to relay data back to the user. The cause for this is that water heavily absorbs most electromagnetic signals, preventing effective radio communication over large distances, and that underwater communication with acoustic signals affords only bit rates on the the order of Kilobits per second. In this thesis we present a novel design and implementation for an underwater data muling system. This system allows for automatic collection of underwater datasets without the need to physically connect to or move the sensors by using mobile robots to travel to the sensors and download the data using wireless optical communication to bring it back to the base station. The system consists of two parts. The first part is a modular and adaptive robot for underwater locomotion in six degrees of freedom. We present a hardware design as well as control algorithms to allow for in-situ deployment without the need for manual configuration of the parameter space. To achieve this we designed a highly parameterizable controller and methods and algorithms for automatically estimating all parameters of this controller. The second part of the data mulling system is a novel high-bandwidth optical underwater communication device. This device allows for transfer of high-fidelity data, such as high-definition video and audio, images, and sensor logs. Finally we present algorithms to control the robots path in order to maximize data rates as it communicates with a sensor while using only the signal strength as a measurement. All components and algorithms of the system have been implemented and tested in the real world to demonstrate the validity of our claims.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
 
Cataloged from PDF version of thesis.
 
Includes bibliographical references (p. 187-197).
 
Date issued
2013
URI
http://hdl.handle.net/1721.1/79211
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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