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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Bibliographic Details
Published inProceedings 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
Main Authors Fukuda, T., Sekiyama, K., Takagawa, I., Shibata, S., Yamamoto, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1999
Subjects
Electric breakdown
Genetic algorithms
Intelligent manufacturing systems
Learning automata
Machining
Manufacturing systems
Production systems
Switches
Technology management
Transportation
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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.
ISBN:0780351843
9780780351844
DOI:10.1109/IROS.1999.813037