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dc.contributor.advisorHenrik Schmidt.en_US
dc.contributor.authorSchneider, Toby Edwinen_US
dc.contributor.otherWoods Hole Oceanographic Institution.en_US
dc.date.accessioned2013-06-17T19:04:24Z
dc.date.available2013-06-17T19:04:24Z
dc.date.copyright2013en_US
dc.date.issued2013en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/79162
dc.descriptionThesis (Ph. D.)--Joint Program in Oceanography/Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2013.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 151-161).en_US
dc.description.abstractAutonomous marine vehicles are increasingly used in clusters for an array of oceanographic tasks. The effectiveness of this collaboration is often limited by communications: throughput, latency, and ease of reconfiguration. This thesis argues that improved communication on intelligent marine robotic agents can be gained from acting on knowledge gained by improved awareness of the physical acoustic link and higher network layers by the AUV's decision making software. This thesis presents a modular acoustic networking framework, realized through a C++ library called goby-acomms, to provide collaborating underwater vehicles with an efficient short-range single-hop network. goby-acomms is comprised of four components that provide: 1) losslessly compressed encoding of short messages; 2) a set of message queues that dynamically prioritize messages based both on overall importance and time sensitivity; 3) Time Division Multiple Access (TDMA) Medium Access Control (MAC) with automatic discovery; and 4) an abstract acoustic modem driver. Building on this networking framework, two approaches that use the vehicle's "intelligence" to improve communications are presented. The first is a "non-disruptive" approach which is a novel technique for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. This system was analyzed on experimental data and implemented on a fielded vehicle. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-bit integer baseline, was achieved. The second approach is "disruptive," as it changes the vehicle's course to effect an improvement in the communications channel. A hybrid data- and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication.en_US
dc.description.statementofresponsibilityby Toby Edwin Schneider.en_US
dc.format.extent161 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.subjectJoint Program in Oceanography/Applied Ocean Science and Engineering.en_US
dc.subjectWoods Hole Oceanographic Institution.en_US
dc.titleAdvances in integrating autonomy with acoustic communications for intelligent networks of marine robotsen_US
dc.typeThesisen_US
dc.description.degreePh.D.en_US
dc.contributor.departmentJoint Program in Oceanography/Applied Ocean Science and Engineeringen_US
dc.contributor.departmentWoods Hole Oceanographic Institutionen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineering
dc.identifier.oclc846911500en_US


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