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Hugh Herr. Furtney, Matthew D Program in Media Arts and Sciences (Massachusetts Institute of Technology) Program in Media Arts and Sciences (Massachusetts Institute of Technology) 2016-12-22T16:27:09Z 2016-12-22T16:27:09Z 2016 2016 http://hdl.handle.net/1721.1/106056 964701566 Thesis: S.M., Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 72-73). In this thesis we present a novel approach to the computer simulation of forward dynamic gait models and the optimization of parameters that must be tuned for such models. This methodology is not limited to gait simulation, and could be useful for any situation in which a complex Simulink model requires variables to be tuned via machine learning to optimize all heuristic that can only be evaluated via simulation. Through the lens of Biomechatronic engineering research, we combine the fundamentals of software engineering with a refinement of the best practices of Matlab and Simulink programming and a working knowledge of inherent Matlab and Simulink constraints to construct a framework for rapid model development. Key features of this methodology include: the use of Simulink as an environment for rapidly prototyped models, the use of and construction of custom Simulink libraries, and use of the Matlab Optimization Toolbox. This methodology uses parallel evaluation of rapid acceleration Simulink executables to minimize optimization time, and allow research teams to take advantage of parallel processing and cloud computing. This methodology was applied to a bouncing gait model developed by Hartmut Geyer for evaluation. We demonstrate its effectiveness by simulating this model using a custom library of model components, such as ground contact model, Stateflow control, heuristic computation, and body segments. by Matthew D. Furtney. S.M. 73 pages eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Program in Media Arts and Sciences () Modular engineering of neuromuscular gait simulators Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="671a11a2-dca8-4932-adcb-577440788ca0"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Modular engineering of neuromuscular gait simulators</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2016</PublicationDate> <Authors> <Author> <DisplayName>Furtney, Matthew D</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Program in Media Arts and Sciences ()</Keyword> <Abstract>In this thesis we present a novel approach to the computer simulation of forward dynamic gait models and the optimization of parameters that must be tuned for such models. This methodology is not limited to gait simulation, and could be useful for any situation in which a complex Simulink model requires variables to be tuned via machine learning to optimize all heuristic that can only be evaluated via simulation. Through the lens of Biomechatronic engineering research, we combine the fundamentals of software engineering with a refinement of the best practices of Matlab and Simulink programming and a working knowledge of inherent Matlab and Simulink constraints to construct a framework for rapid model development. Key features of this methodology include: the use of Simulink as an environment for rapidly prototyped models, the use of and construction of custom Simulink libraries, and use of the Matlab Optimization Toolbox. This methodology uses parallel evaluation of rapid acceleration Simulink executables to minimize optimization time, and allow research teams to take advantage of parallel processing and cloud computing. This methodology was applied to a bouncing gait model developed by Hartmut Geyer for evaluation. We demonstrate its effectiveness by simulating this model using a custom library of model components, such as ground contact model, Stateflow control, heuristic computation, and body segments.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>