Neural Network Driven Automated Guided Vehicle Platform Development for Industry 4.0 Environment
This work presents the development of a new "Two Wheel" Automated Guided Vehicle (AGV) platform for education, competition, and research that is based on sensor fusion and neural networks (NN) with machine learning for Industry 4.0 applications. The method that is described in the paper de...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/263d766b8354468ea6699c6b768c5126 |
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| Sumario: | This work presents the development of a new "Two Wheel" Automated Guided Vehicle (AGV) platform for education, competition, and research that is based on sensor fusion and neural networks (NN) with machine learning for Industry 4.0 applications. The method that is described in the paper deals with intelligent path planning and navigation of an AGV that should move safely in an unknown environment. The unknown environment may have obstacles of arbitrary shape and size that can move. Also is described the approach to solving the navigation problem in AGV navigation using a neural networks-based technique based on various types of input sensors. The neural network determines the safe direction for the next point section of the path in the environment while avoiding the nearby obstacles. Simulation examples of the generated path with proposed techniques will be presented. |
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