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    A Neurorobotic Model of Humanoid Walking

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    Author
    Klein, Theresa Jean
    Issue Date
    2011
    Keywords
    central pattern generator
    neurorobotic
    walking
    Electrical & Computer Engineering
    biarticular
    biped
    Advisor
    Lewis, Anthony M.
    
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    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    In this dissertation, we describe the development of a humanoid bipedal robot that fully physically models the human walking system, including the biomechanics of the leg, the sensory feedback pathways available in the body, and the neural structure of the central pattern generator (CPG). Using two different models of the CPG, we explore several issues in the neurobiology and robotics literature, including the role of reflexes in locomotion, the role of load reception and positive force feedback in generating the gait, and the degree to which central or peripheral control plays in human walking. We show that the walking pattern can be generated by a combination of a half-center CPG and reflex interactions phase modulated by the CPG, and that load receptors in the muscles can play a substantial role in generating the gait, using positive force feedback. We compare the gait of the robot to human subjects and show that this architecture produces human-like stepping. Varying the degree of direct central control of lower limb muscles by the CPG, we show that the most human-like gait is generated with a relatively weak central control signal, which modulates reflex responses that generate most of the muscle activation. These results allow us to conceive of locomotion as a series of nested loops, with a central CPG or rhythm generator modulating lower level reflex interactions, while higher centers modulate the CPG. Since locomotion is a primary mechanism by which animals interact with the world, this research is relevant to artificial intelligence researchers. Recent understanding of cognition holds that minds are embodied, situated relative to a set of goals, and exist in a feedback loop of interaction with the environment. In our robot, we model the dynamics of the body, the neural architecture and the sensory feedback channels in a complete dynamical feedback loop, and show that the robot entrains to the the natural dynamics of the world. We propose the concept of nested loops with descending phase modulation as a conceptual paradigm for a more general understanding of nervous system organization.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Electrical & Computer Engineering
    Degree Grantor
    University of Arizona
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