Task-Based Mass Optimization of Reconfigurable Robotic Manipulator Systems

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.

Department dc:contributor.department

Aerospace Engineering

Year dc:date.issued

2006

Author dc:creator

• Koelln, Nathan Thomas

Advisor dc:contributor.advisor

• Akin, David L

Language dc:language.iso

en_US

Handle dc:identifier.uri

http://hdl.handle.net/1903/3943

OAI identifier oai:identifier

oai:drum.lib.umd.edu:1903/3943