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Filtering by: Creator Sukhatme, Gaurav S. Remove constraint Creator: Sukhatme, Gaurav S. Non-Academic Affiliation Oregon State University. Collaborative Robotics and Intelligent Systems (CoRIS) Institute Remove constraint Non-Academic Affiliation: Oregon State University. Collaborative Robotics and Intelligent Systems (CoRIS) Institute

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  • 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:
    Prasad Tadepalli for their insightful comments on the technical details of this work and to Gaurav

  • Realizable Path Planning and Execution for Robotic Systems

    Creator:
    Jones, Dylan A.
    Abstract:
    Performing autonomous robotic tasks in the field, such as ocean monitoring and aerial surveillance, requires planning and executing paths in dynamic environments. In these uncertain and changing environments, it is not uncommon to see a large difference between the path planned by the robotic vehicle and the path that the...
    Resource Type:
    Dissertation

  • 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:
    - tegrated into Agent 0’s population at epoch 20, Agent 0 overcomes the environmental difficulty causing both

  • 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
    Full Text:
    around each smax and smin ∈ S Fig 5.1c shows the merging of adjacent maxima regions and the creation of

  • Towards Annotation-Efficient Video Representation Learning

    Creator:
    Patravali, Jay Sanjay
    Abstract:
    Labeling videos is costly, time-consuming and tedious. These costs can escalate in applications such as medical diagnosis or autonomous driving where we need domain expertise for annotation. Few-shot action recognition aims to solve this problem by annotation-efficient learning mechanisms. This thesis presents MetaUVFS as the first Unsupervised Meta-learning algorithm for...
    Resource Type:
    Masters Thesis
    Full Text:
    this work. I am thankful to my manager and colleagues at Microsoft - Mei Chen, Gaurav Mittal, and Ye

  • Topological Learning for Robotic Exploration and Navigation in Uncertain Environments

    Creator:
    Saroya, Manish R.
    Abstract:
    The effectiveness of robot autonomy is governed by the ability to make decisions based on online sensor measurements and a prior belief of the environment. Uncertainty in the environment introduces challenges to robotic decision making. This thesis address two key robot decision making problems: exploration and navigation. The robotic exploration...
    Resource Type:
    Masters Thesis
    Full Text:
    at Oregon State University. I would like to thank Kush Prasad for providing guidance and Gaurav

  • Counterfactual thinking applied to multiagent systems

    Creator:
    Zerbel, Nicholas
    Abstract:
    Multiagent approaches are well suited to designing autonomous solutions for systems that feature complex interactions between many individuals such as in autonomous traffic systems and multi-robot exploration systems. However, creating autonomous agents that function effectively in these systems is a challenging task. In these complex environments, agents need informative reward...
    Resource Type:
    Dissertation