Aufsatzsammlung
Automated guided vehicle systems : internat. trends in manufacturing technology
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISBN
-
9783540174325
354017432X
9780387174327
038717432X
9780948507274
0948507276
- Dimensions
-
25 cm
- Extent
-
361 S.
- Language
-
Englisch
- Notes
-
Ill., graph. Darst.
Literaturangaben
- Keyword
-
Fahrerloses Transportsystem
Automatisches Transportsystem
Transportarbeiten
Automated Transfer Vehicle
Transportarbeiter
- Event
-
Veröffentlichung
- (where)
-
Kempston, Bedford, Berlin, Heidelberg, New York, London, Paris, Tokyo
- (who)
-
IFS (Publ.), Springer
- (when)
-
1987
- Contributor
- Table of contents
- Rights
-
Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.
- Last update
-
11.03.2025, 11:48 AM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Aufsatzsammlung
Associated
- Hollier, Robert H.
- IFS (Publ.), Springer
Time of origin
- 1987
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Selection of optimal machine learning algorithm for autonomous guided vehicle’s control in a smart manufacturing environment
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Automated generation of roadmaps for automated guided vehicle systems
AGVS at work : automated guided vehicle systems
Automated guided vehicle systems : a primer with practical applications
Automated guided vehicles
A new memetic algorithm for mitigating tandem automated guided vehicle system partitioning problem
Automated Vehicle Location (AVL)
Automated guided vehicle systems : a guide - with practical applications - about the technology - for planning
Proceedings of the 4th International Conference on Automated Guided Vehicle Systems : 24 - 26 June 1986, Chicago USA
Machine intelligence : an internat. bibliography with abstracts of sensors in automated manufacturing
Smart maintenance architecture for automated guided vehicles
Selection of optimal machine learning algorithm for autonomous guided vehicle’s control in a smart manufacturing environment