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Filtering by: Creator Shakun, Jeremy D. Remove constraint Creator: Shakun, Jeremy D. Degree Field Robotics Remove constraint Degree Field: Robotics

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  • Practical Reinforcement Learning for Bipedal Locomotion

    Creator:
    Dao, Jeremy
    Abstract:
    Reinforcement learning has emerged as a popular tool for solving control tasks, with multiple works focusing on the complex and dynamic task of locomotion. However, the naive application of reinforcement learning to this problem often produces maladaptive policies that exploit the model or reward function. This results in behavior that...
    Resource Type:
    Capstone Project
    Full Text:
    by Jeremy Dao A PROJECT submitted to Oregon State University in partial fulfillment of the

  • D₊₊ : Structural Credit Assignment in Tightly Coupled Multiagent Domains

    Creator:
    Rahmattalabi, Aida
    Abstract:
    Autonomous multiagent teams can be used in complex exploration tasks to both expedite the exploration and improve the efficiency. However, use of multiagent systems presents additional challenges. Specifically, in domains where the agents' actions are tightly coupled, coordinating multiple agents to achieve cooperative behavior at the group level is difficult....
    Resource Type:
    Masters Thesis
    Full Text:
    degree of Master of Science in Robotics presented on August 2, 2016. Title: D++: Structural Credit

  • Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

    Creator:
    Green, Kevin
    Abstract:
    Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...
    Resource Type:
    Dissertation
    Full Text:
    , faster than I could have ever imagined. To Helei Duan, Jeremy Dao, Mike Hector, and Brian Layng for

  • 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
    Full Text:
    Abstract approved: William D. Smart Numerous diseases and injuries can limit a person’s ability to

  • Privacy-Sensitive Robotics

    Creator:
    Rueben, Matthew R.
    Abstract:
    This dissertation focuses on personal privacy in human-robot interaction, which we call "privacy-sensitive robotics." Our understanding of "privacy" is very broad, including not just information privacy but also physical, psychological, and social privacy. We begin by surveying the scholarly literature on privacy and talking about why it applies to interactions...
    Resource Type:
    Dissertation
    Full Text:
    Robotics Abstract approved: William D. Smart This dissertation focuses on personal privacy in human

  • 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
    Full Text:
    -Dimensional Reinforcement Learning with Human Feedback Abstract approved: William D. Smart Prasad Tadepalli

  • Robust Long Term Autonomy Through Local Behaviors

    Creator:
    Yates, Connor L.
    Abstract:
    Multi-robot teams offer promising solutions for many long term deployments in remote and dangerous domains, such as extraterrestrial or underseas exploration. However, long term deployments present many problems preventing robot teams from operating effectively. Learning over long time scales is makes it difficult to assign credit to robots' actions, as...
    Resource Type:
    Dissertation
    Full Text:
    will only equal 1 if and only if B-type and D- type POIs have been observed

  • Learning to coordinate in sparse asymmetric multiagent systems

    Creator:
    Dixit, Gaurav
    Abstract:
    Multiagent learning offers a rich framework to address challenging real-world problems such as remote exploration and healthcare coordination, which require autonomous agents to express elaborate interactions. To be effective in such systems, agents must collectively reason about and pursue high-level, long-term, and possibly nebulous objectives while adapting their strategy to...
    Resource Type:
    Dissertation
    Full Text:
    complementary specializations required for robust teamwork. The first contribution, Asymmetric D++, distills

  • Robust Reference-Free Sim-to-Real Reinforcement Learning for Bipedal Locomotion

    Creator:
    Siekmann, Jonah A.
    Abstract:
    In recent years, model-free Deep Reinforcement Learning (RL) has become an increasingly popular alternative to more traditional model-based or optimization-based control methods in solving robotic legged locomotion. However, deploying RL in the real world can be a significant undertaking. Constructing reward functions which compel controllers to learn the desired behavior...
    Resource Type:
    Masters Thesis
    Full Text:
    ACKNOWLEDGEMENTS I would like to thank Kevin Green, Yesh Godse, Helei Duan, and Jeremy Dao for their advice

  • Agile Bipedal Maneuvers Optimized then Learned from Single Rigid-Body Model Dynamics

    Creator:
    Batke, Ryan
    Abstract:
    As bipedal robots move ever closer to being integrated into all manner of real world envi-ronments there is a necessity to push their dynamic capabilities to meet or exceed those of humans and animals. Advancements must be made to address ordinary challenges that arise everyday in the same environments that...
    Resource Type:
    Masters Thesis
    Full Text:
    hand or ear. I would also like to extend special thanks to Jeremy Dao for his patience and help