Cycle-based Robot Drive Train Optimization Utilizing SVD Analysis
2008 (English)In: ASME Design Automation Conference,2007, Las Vegas: ASME , 2008, 903-910 p.Conference paper (Refereed)
Designing a drive train for an industrial robot is a demanding task where a set of design variables need to be determined so that optimal performance is obtained for a wide range of different duty cycles. The paper presents a method where singular value decomposition (SVD) is used to reduce the design variable set. The application is a six degree of freedom serial manipulator, with nine drive train parameters for each axis and the objective is to minimize the cycle time on 122 representative design cycles without decreasing the expected lifetime of the robot. The optimization is based on a simulation model of the robot and conducted on a reduced set of the initial duty cycles and with the design variables suggested by the SVD analysis. The obtained design reduces the cycle time with 1.6% on the original design cycles without decreasing the life time of the robot.
Place, publisher, year, edition, pages
Las Vegas: ASME , 2008. 903-910 p.
Engineering and Technology
IdentifiersURN: urn:nbn:se:liu:diva-39784DOI: 10.1115/DETC2007-34772ISI: 000254345300081Local ID: 51216ISBN: 0-7918-3806-4 (online)ISBN: 0-7918-4807-8 (print)OAI: oai:DiVA.org:liu-39784DiVA: diva2:260633
ASME International Design Engineering Technical Conferences/Computers and Information in Engineering Conference