MATEC Web Conf.
Volume 299, 2019Modern Technologies in Manufacturing (MTeM 2019)
|Number of page(s)||6|
|Section||Automation of Manufacturing Systems and Assembly|
|Published online||02 December 2019|
Innovative Solutions of the Automated Guided Vehicles in Industrial Manufacturing
Technical University of Cluj-Napoca, Department of Manufacturing Engineering,
Muncii Blvd 103-105,
* Corresponding author: email@example.com
The Automated Guided Vehicle (AGV) is a mobile device that is used in the manufacturing plants lately for transporting materials from one space to another. AGVs are connected to a central navigation system which continuously directs the device to its source or destination. Their main features are their flexibility and adaptability to the environment once the AGVs are configured. The main focus of this article is to present the AGV technology based on vision navigation system reinforced by programming code and navigation graphs with the scope of adhering to the latest innovative concepts in terms of efficiency and optimized manufacturing. The topic of vision-based systems being recent to the engineeringevolution, several academicians have discussed probabilities for improvement: some introduce the concept of an independent robot which can learn through artificial intelligence about the dynamic environment or others state, that a neural network can be used in the future as the basis for movement of the AGV in the workspace.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.