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Akin, David L Koelln, Nathan Thomas Digital Repository at the University of Maryland University of Maryland (College Park, Md.) Aerospace Engineering 2006-09-12T06:08:08Z 2006-09-12T06:08:08Z 2006-09-01 http://hdl.handle.net/1903/3943 This 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. 1731668 bytes application/pdf en_US Task-Based Mass Optimization of Reconfigurable Robotic Manipulator Systems Thesis Engineering, Aerospace Reconfigular Robotics Modular Robotics Genetic Algorithm On-Orbit Servicing open.access