Accession Number : ADA612632


Title :   Autonomous & Adaptive Oceanographic Feature Tracking on Board Autonomous Underwater Vehicles


Descriptive Note : Doctoral thesis


Corporate Author : WOODS HOLE OCEANOGRAPHIC INSTITUTION MA


Personal Author(s) : Petillo, Stephanie M


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a612632.pdf


Report Date : Feb 2015


Pagination or Media Count : 219


Abstract : The capabilities of autonomous underwater vehicles (AUVs) and their ability to perform tasks both autonomously and adaptively are rapidly improving, and the desire to quickly and efficiently sample the ocean environment as Earth's climate changes and natural disasters occur has increased significantly in the last decade. As such, this thesis proposes to develop a method for single and multiple AUVs to collaborate autonomously underwater while autonomously adapting their motion to changes in their local environments, allowing them to sample and track various features of interest with greater efficiency and synopticity than previously possible with preplanned AUV or ship-based surveys. This concept is demonstrated to work in field testing on multiple occasions: with a single AUV autonomously and adaptively tracking the depth range of a thermocline or acousticline, and with two AUVs coordinating their motion to collect a data set in which internal waves could be detected. This research is then taken to the next level by exploring the problem of adaptively and autonomously tracking spatiotemporally dynamic underwater fronts and plumes using individual and autonomously collaborating AUVs.


Descriptors :   *ADAPTIVE SYSTEMS , *OCEAN ENVIRONMENTS , *TRACKING , *UNDERWATER VEHICLES , CLIMATE , DATA BASES , DYNAMICS , EFFICIENCY , INTERNAL WAVES , MOTION , NATURAL DISASTERS , OCEANOGRAPHY , SELF OPERATION , SHIPBOARD , SURVEYS , THERMOCLINES , THESES , UNDERWATER


Subject Categories : Physical and Dynamic Oceanography
      Submarine Engineering


Distribution Statement : APPROVED FOR PUBLIC RELEASE