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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 |
| Appears in Collections: | Fulltext Publications |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Parallel-populations genetic algorithm for the optimization of cubic polynomial joint trajectories for industrial robots.pdf | 804.83 kB | Adobe PDF | View/Open |
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