Hybrid approach of genetic algorithms and learning automata for flexible transfer system
The flexible transfer system (FTS) is a self-organizing manufacturing system composed of autonomous robotic modules, which transfer a palette carrying machining parts. The central issue is realization of both higher efficiency and flexibility to cope with environmental change, such as a sudden chang...
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Published in | Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289) Vol. 1; pp. 400 - 405 vol.1 |
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Main Authors | , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
1999
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Subjects | |
Online Access | Get full text |
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Summary: | The flexible transfer system (FTS) is a self-organizing manufacturing system composed of autonomous robotic modules, which transfer a palette carrying machining parts. The central issue is realization of both higher efficiency and flexibility to cope with environmental change, such as a sudden change of machining plan or breakdowns of the modules. Through the self-organization of a multi-layered strategic vector field corresponding to a task, the FTS can generate a quasi-optimal transfer path with learning automata. Also, the optimal planning is attempted by use of genetic algorithms, and is based on the global information on the system. We propose a hybridization method between the distributed and centralized approaches. Simulation is conducted to evaluate the basic system performance and the results show the effectiveness. |
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ISBN: | 0780351843 9780780351844 |
DOI: | 10.1109/IROS.1999.813037 |