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Filtering by: Creator Maina, Geoffrey M. Remove constraint Creator: Maina, Geoffrey M. Degree Field Robotics Remove constraint Degree Field: Robotics

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  • Communication Planning for Cooperative Terrain-Based Underwater Localization

    Creator:
    Anderson, Jacob
    Abstract:
    This thesis presents a decentralized communication planning algorithm for cooperative terrain-based navigation (dec-TBN) with autonomous underwater vehicles. The proposed algorithm uses forward simulation to approximate the value of communicating at each time step. The simulations are used to build a directed acyclic graph that can be searched to provide a...
    Resource Type:
    Masters Thesis

  • Deployment Planning for Multiple Marsupial Robots

    Creator:
    Lee, Chris (Yu Hsuan)
    Abstract:
    Multi-robot systems are versatile and extremely capable of exploration tasks in complex environments. Increasingly sophisticated planners, which incorporate new features of a multi-robot system, are necessary for the operation of the systems. Marsupial robots are multi-robot systems consisting of a carrier robot (e.g., a ground vehicle), which is highly capable...
    Resource Type:
    Masters Thesis
    Full Text:
    Multiple Marsupial Robots Abstract approved: Geoffrey Hollinger Multi-robot systems are versatile and

  • 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
    Full Text:
    Exploration Abstract approved: Geoffrey A Hollinger Emerging applications for robotic data collection

  • Efficiently Learning Human Preferences for Robot Autonomy

    Creator:
    Somers, Thane N.
    Abstract:
    Human-robot teams are invaluable for mapping unknown environments, exploring difficult-to-reach areas, and manipulating inaccessible equipment. However, guiding autonomous robots requires dealing with these dynamic domains while synthesizing a significant amount of data and balancing competing objectives. Current mission planning methods often involve manually specifying low-level parameters of the mission, such...
    Resource Type:
    Masters Thesis
    Full Text:
    Human Preferences for Robot Autonomy Abstract approved: Geoffrey A. Hollinger Human-robot teams are

  • Modeling human expertise for providing adaptive levels of robot shared autonomy

    Creator:
    Milliken, Lauren
    Abstract:
    In shared autonomy, a robot and human user both have some level of control in order to achieve a shared goal. Choosing the balance of control given to the user and the robot can be a challenging problem since different users have different preferences and vary in skill levels when...
    Resource Type:
    Masters Thesis
    Full Text:
    Providing Adaptive Levels of Robot Shared Autonomy Abstract approved: Geoffrey A Hollinger In shared

  • 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

  • Model Predictive Control for Underwater Robots in Ocean Waves

    Creator:
    Fernández, Daniel C.
    Abstract:
    Underwater robots beneath ocean waves can benefit from feedforward control to reduce position error. This thesis proposes a method using Model Predictive Control (MPC) to predict and counteract future disturbances from an ocean wave field. The MPC state estimator employs a Linear Wave Theory (LWT) solver to approximate the component...
    Resource Type:
    Masters Thesis
    Full Text:
    Waves Abstract approved: Geoffrey A. Hollinger Underwater robots beneath ocean waves can benefit from

  • 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
    Full Text:
    Abstract approved: Geoffrey A. Hollinger Deep learning has recently revolutionized robot perception in

  • Planning Under Uncertainty for Unmanned Aerial Vehicles

    Creator:
    Skeele, Ryan
    Abstract:
    Unmanned aerial vehicle (UAV) technology has grown out of traditional research and military applications and has captivated the commercial and consumer markets, showing the ability to perform a spectrum of autonomous functions. This technology has the capability of saving lives in search and rescue, fighting wildfires in environmental monitoring, and...
    Resource Type:
    Masters Thesis
    Full Text:
    Unmanned Aerial Vehicles Abstract approved: Geoffrey Hollinger Unmanned aerial vehicle (UAV) technology