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