{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/70436"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/70436","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Infrastructure for large-scale tests in marine autonomy","abstract":"This thesis focuses on the development of infrastructure for research with large-scale autonomous marine vehicle fleets and the design of sampling trajectories for compressive sensing (CS). The newly developed infrastructure includes a bare-bones acoustic modem and two types of low-cost and scalable vehicles. One vehicle is a holonomic raft designed for station-keeping and precise maneuvering, and the other is a streamlined kayak for traveling longer distances. The acoustic modem, like the vehicles, is inexpensive and scalable, providing the capability of a large-scale, low-cost underwater acoustic network. With these vehicles and modems we utilize compressive sensing, a recently developed framework for sampling sparse signals that offers dramatic reductions in the number of samples required for high fidelity reconstruction of a field. Our novel CS sampling techniques introduce engineering constraints including movement and measurement costs to better apply CS to sampling with mobile agents. The vehicles and modems, along with compressive sensing, strengthen the movement towards large scale autonomy in the ocean environment.","abstract_html":"This thesis focuses on the development of infrastructure for research with large-scale autonomous marine vehicle fleets and the design of sampling trajectories for compressive sensing (CS). The newly developed infrastructure includes a bare-bones acoustic modem and two types of low-cost and scalable vehicles. One vehicle is a holonomic raft designed for station-keeping and precise maneuvering, and the other is a streamlined kayak for traveling longer distances. The acoustic modem, like the vehicles, is inexpensive and scalable, providing the capability of a large-scale, low-cost underwater acoustic network. With these vehicles and modems we utilize compressive sensing, a recently developed framework for sampling sparse signals that offers dramatic reductions in the number of samples required for high fidelity reconstruction of a field. Our novel CS sampling techniques introduce engineering constraints including movement and measurement costs to better apply CS to sampling with mobile agents. The vehicles and modems, along with compressive sensing, strengthen the movement towards large scale autonomy in the ocean environment.","abstract_has_math":false,"creators":["Hummel, Robert A. (Robert Andrew)"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Mechanical Engineering.","school":null,"contributors":[],"advisors":["Franz S. Hover."],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012","date_published":"2012","updated_at":"2026-07-22T22:20:53Z","subjects":["Mechanical Engineering."],"languages":["eng"],"rights":["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. 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