Theses and Dissertations from UMD

Permanent URI for this communityhttp://hdl.handle.net/1903/2

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    Learning Autonomous Underwater Navigation with Bearing-Only Data
    (2024) Robertson, James; Duraiswami, Ramani; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Recent applications of deep reinforcement learning in controlling maritime autonomoussurface vessels have shown promise for integration into maritime transportation. These could have the potential to reduce at-sea incidents such as collisions and groundings which are majorly attributed to human error. With this in mind the goal of this work is to evaluate how well a similar deep reinforcement learning agent could perform the same task in submarines but using passive SONAR rather than the ranging data provided by active RADAR aboard surface vessels. A simulated submarine outfitted with a passive spherical, hull-mounted SONAR sensor is placed into contact scenarios under the control of a reinforcement learning agent and directed to make its way to a navigational waypoint while avoiding interfering surface vessels. In order to see how this best translates to lower power autonomous vessels (vice warship submarines), no estimation for the range of the surface vessels is maintained in order to cut down on computing requirements. Inspired by my time aboard U.S. Navy submarines, the agent is provided with simply the simulated passive SONAR data. I show that this agent is capable of navigating to a waypoint while avoiding crossing, overtaking, and head-on surface vessels and thus could provide a recommended course to a submarine contact management team in ample time since the maneuvers made by the agent are not instantaneous in contrast to the assumptions of traditional target tracking with bearing-only data. Additionally, an in-progress plugin for Epic Games’ Unreal Engine is presented with the ability to simulate underwater acoustics inside the 3D development software. Unreal Engine is a powerful 3D game engine that is incredibly flexible and capable of being integrated into many different forms of scientific research. This plugin could provide researchers with the ability to conduct useful simulations in intuitively designed 3D environments.
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    Design and Evaluation of End-Effectors for Autonomous Sampling
    (2008-09-16) Lewandowski, Craig Michael; Akin, David; Aerospace Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Autonomous underwater vehicles are becoming increasingly prevalent, and their emergence will allow for the execution of previously unfeasible underwater missions. These missions include seeking naval mines, navigation and mapping of ocean features, and sampling on the ocean floor at extreme depths. One method to achieve this latter objective involves the attachment of a robotic manipulator to an underwater vehicle and use of the manipulator to collect specimens and deposit them in containers. This thesis focuses on the design and testing of an end-effector to be used on such a manipulator. End-effectors previously utilized in underwater robotics were evaluated during the conceptualization of the selected tool design. These evaluations in conjunction with manipulator interface requirements were used to produce the end-effector design that was constructed and subsequently tested. In addition, sample containers were designed and fabricated, and kinematics software used to determine sample container position, orientation, and quantity was developed.