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    Robotic trajectory control employing anyanet neural architecture

    Author
    Simons, Anya L.
    View/Open
    Simons1992.pdf (12.00Mb)
    Other Contributors
    Derby, Stephen J.;
    Date Issued
    1992-12
    Subject
    Engineering science
    Degree
    MS;
    Terms of Use
    This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute (RPI), Troy, NY. Copyright of original work retained by author.;
    Metadata
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    URI
    https://hdl.handle.net/20.500.13015/4961
    Abstract
    Popular and novel neural network architecture and training approaches are combined with conventional trajectory smoothing and obstacle avoidance techniques to demonstrate the feasibility of an industrial robot that can safely, reliably, and effectively interact with humans, avoid unforeseen moving obstacles in a stable fashion, and maintain integrity of its payload. An appreciation is sought for the level of hardware and process integration required for the implementation of a successful comprehensive automated manufacturing package. Extensions of the methods demonstrated are discussed.;
    Description
    School of Engineering; December 1992
    Department
    Publisher
    Rensselaer Polytechnic Institute, Troy, NY
    Relationships
    Access
    Restricted to current Rensselaer faculty, staff and students in accordance with the Rensselaer Standard license. Access inquiries may be directed to the Rensselaer Libraries.;
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