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 re ex 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 humanlike gait is generated with a relatively weak central control signal, which modulates re ex 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 re ex 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.
Some files may require a special program or browser plug-in. More Information
|Advisor:||Lewis, Anthony M.|
|Commitee:||Sanfelice, Ricardo, Tharp, Hal|
|School:||The University of Arizona|
|Department:||Electrical & Computer Engineering|
|School Location:||United States -- Arizona|
|Source:||DAI-B 73/04, Dissertation Abstracts International|
|Subjects:||Neurosciences, Electrical engineering, Robotics|
|Keywords:||Biarticular muscles, Central pattern generator, Legs, Neurorobotic sensory feedback, Walking|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be