Browsing by Author "Williams, Ryan"

Now showing 1 - 4 of 4
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    Future Farmers of Virginia Chapter Chats November 1927
    W. S. N.; Wolfe, T. K.; Clements, D. M.; Beard, Joseph E.; Keister, Joe; E. C. M.; Price, Albert; Smith, Kenneth; Wall, William; Hutton, Andrew; Johnson, Duval; Roach, Everett; Wampler, Ernest; Thornton, Perry; Reid, Joe; Stafford, Horace; Harris, Jr., George A.; Semple, Richard; Buchanan, Chalkley; Walker, Jr., W. Benjamin; Yeatts, Howard; Hubbard, John; Morris, L. W.; Poole, Bert; Monday, Howard; Waterfield, Charlie; Smith, Edward J.; Russell, Dorsey; Russell, Edgar; Whitlow, Billie; Coburn, Robert; Myers, Ross; Bethel, Benjamin; Grubb, Sumpter; Chaffin, Joe; Barham, Montgomery; Hockman, Cecil; Meek, Jack; Stephenson, Ernest; Williams, Ryan; Rhinehart, Stanley; Henry, Mertie (The Future Farmers of Virginia, 1927-11)
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    Learning a Spatial Field in Minimum Time with a Team of Robots
    Suryan, Varun (Virginia Tech, 2018)
    We study an informative path planning problem where the goal is to minimize the time required to learn a spatial field. Specifically, our goal is to ensure that the mean square error between the learned and actual fields is below a predefined value. We study three versions of the problem. In the placement version, the objective is to minimize the number of measurement locations. In the mobile robot version, we seek to minimize the total time required to visit and collect measurements from the measurement locations. A multi-robot version is studied as well where the objective is to minimize the time required by the last robot to return back to a common starting location called depot. By exploiting the properties of Gaussian Process regression, we present constant-factor approximation algorithms that ensure the required guarantees. In addition to the theoretical results, we also compare the empirical performance using a real-world dataset with other baseline strategies.
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    Persistent Monitoring with Energy-Limited Unmanned Aerial Vehicles Assisted by Mobile Recharging Stations
    Yu, Kevin L. (Virginia Tech, 2018)
    We study the problem of planning a tour for an energy-limited Unmanned Aerial Vehicle (UAV) to visit a set of sites in the least amount of time. We envision scenarios where the UAV can be recharged along the way either by landing on stationary recharging stations or on Unmanned Ground Vehicles (UGVs) acting as mobile recharging stations. This leads to a new variant of the Traveling Salesperson Problem (TSP) with mobile recharging stations. We present an algorithm that finds not only the order in which to visit the sites but also when and where to land on the charging stations to recharge. Our algorithm plans tours for the UGVs as well as determines the best locations to place stationary charging stations. While the problems we study are NP-Hard, we present a practical solution using Generalized TSP that finds the optimal solution. If the UGVs are slower, the algorithm also finds the minimum number of UGVs required to support the UAV mission such that the UAV is not required to wait for the UGV. We present a calibration routine to identify parameters that are needed for our algorithm as well as simulation results that show the running time is acceptable for reasonably sized instances in practice. We evaluate the performance of our algorithm through simulations and proof-of-concept experiments with a fully autonomous system of one UAV and UGV.
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    System Synthesis Supplementary Data
    Ziglar, Jason; Williams, Ryan; Wicks, Alfred L. (Virginia Tech, 2018-02-22)
    Introduction In order to explore the capability of automated system synthesis to compose a variety of novel systems from a common set of components, an experiment simulating the design of a mobile search and rescue robotic system is developed. As an automated system synthesis experiment, this experiment explores how an automated system can generate the structure of an design which can be implemented with a defined set of components available to satisfy the design; the components used in these designs are taken as an input into the system. Thus, this document describes the defined components used in this experiment, as well as how the experiments were organized and executed, with the system performance both in terms of computational requirements and resulting designs reported. The formulation of the system synthesis approach used in these experiments are described in work referencing this document. This experiment defines a variety of common hardware and software components which may be useful for the implementation of the proposed robotic system in a variety of operating conditions. These components are based on describing components developed or used for real world components developed for a variety of previous robotics research projects. This experiment also defines a set of functional capabilities which may be included in the system, as well as a set of environmental parameters which may impact how such functionality must be implemented. These components include some components which provide similar functional capabilities with varying non-functional requirements (e.g. differing types of connection standards, differing computational resource budgets/requirements) in order to flesh out the design space such that trade-offs between selections exist.