| Issue |
E3S Web Conf.
Volume 501, 2024
International Conference on Computer Science Electronics and Information (ICCSEI 2023)
|
|
|---|---|---|
| Article Number | 01006 | |
| Number of page(s) | 5 | |
| Section | Applied Computer Science and Electronics for sustainability | |
| DOI | https://doi.org/10.1051/e3sconf/202450101006 | |
| Published online | 18 March 2024 | |
Automatic berthing systems: a review on artificial intelligence methods for marine ship
1 Research Scholar/Electro Technical officer@Kotc, Kalasalingam Academy of Research and Education, Anand Nagar, Krishnankoil – 626 126, India
2 Associate Professor, Department of Electrical and Electronics Engineering, Kalasalingam Academy of Research and Education, Anand Nagar, Krishnankoil - 626 126, India
3 ASCEE Computer Society, Association for Scientific Computing Electronics and Engineering (ASCEE), Indonesia
* Corresponding author: eeepmuthu@gmail.com
One of the most challenging issues in the world of ship control is automatic ship berthing. In order for the berthing to be completed automatically and safely, the control systems must account for the ship’s dynamics at low speeds. Artificial neural networks (ANNs) are frequently used to address this need because of their capacity to mimic and carry out all the functions of the human brain throughout the ship berthing procedure. However, there are still certain drawbacks when employing this theory to create the automatic system for ship berthing, and this makes it more challenging to develop the control system for practical ship applications. This study reviews the pros and cons of employing ANNs along with some other deep learning algorithms in automatic ship berthing systems. Some directions for further research into automatic ship-berthing systems are also suggested.
© The Authors, published by EDP Sciences, 2024
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