Optical tracking system for automatic guided vehicles using cellular neural networks
| Autor: | J. Bito, J. Vass, András Kiss, G. Eross, Tamás Roska, T. Boros, András Radványi |
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| Rok vydání: | 2003 |
| Předmět: |
Very-large-scale integration
Artificial neural network business.industry Computer science Optical computing ComputerApplications_COMPUTERSINOTHERSYSTEMS Fault tolerance Computer-integrated manufacturing Robustness (computer science) Embedded system Control system Cellular neural network business Computer hardware |
| Zdroj: | CNNA '92 Proceedings Second International Workshop on Cellular Neural Networks and Their Applications. |
| DOI: | 10.1109/cnna.1992.274366 |
| Popis: | A method for the path-control of automated guided vehicles (AGVs) in computer integrated manufacturing (CIM) systems that combines the flexibility and easy installation of optical methods with the simplicity and robustness of the inductive method is proposed. Using a new computing paradigm, the cellular neural network (CNN), and a related device, the VLSI CNN chip, a very high speed solution that is less expensive than the conventional methods can be achieved. This AGV control complies with the requirements of CIM systems. Further advantages of the proposed system are as follows: fault tolerance and the ability to give instructions along the path, and the use of a simple local control. > |
| Databáze: | OpenAIRE |
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