Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/7691
Title: Parallel-populations genetic algorithm for the optimization of cubic polynomial joint trajectories for industrial robots
Authors: Abu-Dakka, Fares J. 
Assad, Iyad F. 
Valero, Francisco 
Mata, Vicente 
Keywords: Robots, Industrial - Design and construction;Industrial robotics - Design and construction;Automation;Robots - Motion
Issue Date: 2011
Publisher: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Abstract: The main objective of this paper is to obtain minimum-time trajectories for industrial robots using parallel populations genetic algorithms. Subjected to: ▪ Physical constraints: joint velocities, accelerations, and jerks. ▪ Dynamic constraints
URI: http://hdl.handle.net/20.500.11889/7691
DOI: 10.1007/978-3-642-25486-4_9
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