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Infrastructure for Large-Scale Tests in Marine Autonomy

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...

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Main Author: Hummel, Robert A
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description 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 streamlined kayak for travelling 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 a 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.
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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 streamlined kayak for travelling 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 a better apply CS to sampling with mobile agents. 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source DTIC Technical Reports
subjects AUTONOMOUS NAVIGATION
GROUND VEHICLES
INFRASTRUCTURE
MARINE CORPS EQUIPMENT
Navigation and Guidance
OCEAN ENVIRONMENTS
PARALLEL PROCESSING
Surface Transportation and Equipment
TRAVELING WAVES
UNDERWATER COMMUNICATIONS
title Infrastructure for Large-Scale Tests in Marine Autonomy
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