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Filtering by: Creator Attardo, Geoffrey M. Remove constraint Creator: Attardo, Geoffrey M. Degree Field Robotics Remove constraint Degree Field: Robotics Degree Name Doctor of Philosophy (Ph.D.) Remove constraint Degree Name: Doctor of Philosophy (Ph.D.)

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  • Non-Myopic Distributed Coordination and Planning for Robotic Teams

    Creator:
    Smith, Andrew
    Abstract:
    As robotic systems become increasingly prevalent in our lives (e.g., by harvesting food, assisting with disaster response and defense, and transporting persons and our goods around the world) there is a growing need to ensure that they can cooperate to achieve their intended goals. Robotic cooperation in the real-world is...
    Resource Type:
    Dissertation
    Full Text:
    : Non-Myopic Distributed Coordination and Planning for Robotic Teams Abstract approved: Geoffrey A

  • Deep learning for robotic exploration

    Creator:
    Caley, Jeffrey A.
    Abstract:
    Emerging applications for robotic data collection include ocean monitoring, emergency response and urban search and rescue. At the core of these applications is a robot's ability to make informed decisions on incomplete data. This dissertation addresses this problem by developing novel techniques for modeling and estimating structured environments using deep...
    Resource Type:
    Dissertation
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    Exploration Abstract approved: Geoffrey A Hollinger Emerging applications for robotic data collection

  • Augmented Deep Learning Techniques for Robotic State Estimation

    Creator:
    Nicolai, Austin L.
    Abstract:
    While robotic systems may have once been relegated to structured environments and automation style tasks, in recent years these boundaries have begun to erode. As robots begin to operate in largely unstructured environments, it becomes more difficult for them to effectively interpret their surroundings. As sensor technology improves, the amount...
    Resource Type:
    Dissertation
    Full Text:
    Deep Learning Techniques for Robotic State Estimation Abstract approved: Geoffrey A. Hollinger While

  • Deep Perception Without a Camera: Enabling 3D Reconstruction and Object Recognition using Lidar and Sonar Sensing

    Creator:
    DeBortoli, Robert A.
    Abstract:
    Deep learning has recently revolutionized robot perception in many canonical robotic applications, such as autonomous driving. However, a similar transformation has yet to occur in more harsh environments including underwater and underground. This is due in part to the difficulty in deploying robots in these environments, which lack large real...
    Resource Type:
    Dissertation
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    Abstract approved: Geoffrey A. Hollinger Deep learning has recently revolutionized robot perception in

  • Topologically-Guided Robotic Information Gathering

    Creator:
    McCammon, Seth
    Abstract:
    Information gathering tasks, such as terrestrial search and rescue, aerial inspection, and marine monitoring, require robotic unmanned systems to make decisions on how to travel within an environment to maximize or minimize a path-dependent information objective function. The distribution of information throughout the environment is the result of various processes,...
    Resource Type:
    Dissertation
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    -Guided Robotic Information Gathering Abstract approved: Geoffrey A. Hollinger Information gathering

  • Learning-based Techniques for Fast and Robust Motion Planning

    Creator:
    Chow, Scott
    Abstract:
    Motion planning is a cornerstone of autonomous robots, enabling robots to safely and efficiently perform tasks such as package delivery, infrastructure inspection, and manipulation. However, as the field of robotics matures, robotic systems are being developed that (1) are challenging to analytically model, (2) require computationally expensive model-based controllers, and...
    Resource Type:
    Dissertation
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    Techniques for Fast and Robust Motion Planning Abstract approved: Geoffrey A. Hollinger Motion planning is

  • Adaptive Multiagent Traffic Management for Autonomous Robotic Systems

    Creator:
    Rebhuhn, Carrie
    Abstract:
    There is growing commercial interest in the use of unmanned aerial vehicles (UAVs) in urban environments, specifically for package delivery applications. However, the size, complexity and sheer numbers of expected UAVs makes conventional air traffic management that relies on human air traffic controllers infeasible. To enable UAVs to safely and...
    Resource Type:
    Dissertation

  • Structure and Actuation of Cephalopod-Inspired Soft Robots

    Creator:
    Olson, Gina M.
    Abstract:
    Cephalopod-inspired soft robot arms have been studied as a new type of manipulator. These arms have been proposed for reach and grab tasks, underwater locomotion via swimming and walking, and robotic surgery. However, the capabilities of existing soft arms are limited to simple motions and light loads. Arm design has...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Gina M. Olson for

  • High-Dimensional Reinforcement Learning with Human Feedback

    Creator:
    Curran, William
    Abstract:
    State-of-the-art personal robots need to perform complex manipulation tasks to be viable in complex scenarios. However, many of these robots, like the PR2, use manipulators with high degrees of freedom. High degrees of freedom are desirable from a functionality standpoint, but make the learning task more difficult by adding a...
    Resource Type:
    Dissertation

  • Making the Unconscious Unconscious : Reclaiming Microinteractions for People with Motor Disabilities

    Creator:
    Lazewatsky, Daniel A.
    Abstract:
    Numerous diseases and injuries can limit a person's ability to perform everyday tasks -- things like getting dressed, bathing, and eating. Anything that requires physical activity can be affected; even simple things like turning on the lights can become difficult or impossible. Until recently, the only way for a person...
    Resource Type:
    Dissertation
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    (n or m al ize d) total gross fine bulbar resp ALSFRS Decline Figure 2.2: Aggregated ALSFRS