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TitleTask allocation for networked autonomous underwater vehicles
NameKulkarni, Indraneel S. (author), Pompili, Dario (chair), Rutgers University, Graduate School - New Brunswick,
Degree Date2010
Date Created2010
SubjectElectrical and Computer Engineering,
Underwater acoustic telemetry,
Submersibles
DescriptionUnderwater Acoustic Sensor Networks (UW-ASNs) consist of stationary or mobile nodes such as Autonomous Underwater Vehicles (AUVs), which may be classified as propeller-driven vehicles and gliders, that are equipped with a variety of sensors for performing collaborative monitoring tasks. UW-ASNs are envisioned for missions like oceanographic data collection, ocean sampling, offshore exploration, disaster prevention, tsunami and seaquake warning, assisted navigation, distributed tactical surveillance, and mine reconnaissance. A task allocation and optimization framework for networked AUVs that participate as a team to accomplish such missions is developed in this work. These missions entrusted to the AUVs are sometimes critical to human life and property, are bound by severe time and energy constraints, and involve a high degree of inter-vehicular communication. The objective of the framework is to form the best possible team, which is a subset of all deployed AUVs that is best suited to accomplish the mission, while adhering to the constraints. Successful completion of the mission is dependent on effective communication between the networked AUVs and to achieve this a geocasting based networking framework is also proposed. Research specific to this area has been limited. Hence, a framework based on energy minimization for the team of AUVs to complete the mission in given time bound is proposed. Further, the effect of size of geocast region, effect of underwater current on the choice of geocast region and on localized nature of the problem, and the performance of Propeller Driven Vehicles (PDVs) and gliders is compared.
NoteM.S.
NoteIncludes abstract
NoteIncludes bibliographical references
Noteby Indraneel S. Kulkarni
Genretheses
Persistent URLhttp://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000053101
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.