DocumentCode :
1644258
Title :
Optical tracking system for automatic guided vehicles using cellular neural networks
Author :
Eröss, Gy ; Boros, T. ; Kiss, A. ; Radványi, A. ; Roska, T. ; Bitò, J. ; Vass, J.
Author_Institution :
Tungsram TH Co. Ltd., Budapest, Hungary
fYear :
1992
Firstpage :
216
Lastpage :
221
Abstract :
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
Keywords :
VLSI; automatic guided vehicles; cellular arrays; computer integrated manufacturing; computerised materials handling; image processing; neural chips; neural nets; AGVs; CIM; VLSI CNN chip; automatic guided vehicles; cellular neural networks; computer integrated manufacturing; fault tolerance; inductive method; optical tracking system; path-control; Cellular neural networks; Computer integrated manufacturing; Computer networks; Control systems; High speed optical techniques; Integrated optics; Optical computing; Robustness; Vehicles; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Neural Networks and their Applications, 1992. CNNA-92 Proceedings., Second International Workshop on
Conference_Location :
Munich
Print_ISBN :
0-7803-0875-1
Type :
conf
DOI :
10.1109/CNNA.1992.274366
Filename :
274366
Link To Document :
بازگشت