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dc.contributor.advisorAkin, David Len_US
dc.contributor.authorKoelln, Nathan Thomasen_US
dc.date.accessioned2006-09-12T06:08:08Z
dc.date.available2006-09-12T06:08:08Z
dc.date.issued2006-09-01en_US
dc.identifier.urihttp://hdl.handle.net/1903/3943
dc.description.abstractThis work develops a method for implementing task-based mass optimization of modular, reconfigurable manipulators. Link and joint modules are selected from a library of potential parts and assembled into serial manipulator configurations. A genetic algorithm is used to search over the potential set of combinations to find mass-minimized solutions. To facilitate the automatic evaluation required by the genetic algorithm, Denavit-Hartenberg parameters are automatically generated from module combinations. Reconfigurable manipulators are shown to be lighter than fixed-topology manipulators, demonstrating the potential utility of reconfigurable robotics technology for mass reduction in space robots.en_US
dc.format.extent1731668 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleTask-Based Mass Optimization of Reconfigurable Robotic Manipulator Systemsen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentAerospace Engineeringen_US
dc.subject.pqcontrolledEngineering, Aerospaceen_US
dc.subject.pquncontrolledReconfigular Roboticsen_US
dc.subject.pquncontrolledModular Roboticsen_US
dc.subject.pquncontrolledGenetic Algorithmen_US
dc.subject.pquncontrolledOn-Orbit Servicingen_US


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