On the Position Determination of Docking Station for AUVs Using Optical Sensor and Neural Network

International Journal of Engineering and Technology Innovation

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Field Value
 
Title On the Position Determination of Docking Station for AUVs Using Optical Sensor and Neural Network
 
Creator Thieu Quang Minh Nhat
Hyeung-Sik Choi
Mai The Vu
Joono Sur
Jin-Il Kang
Hyun-Joong Son
 
Subject optical sensor
neural network
pinhole camera
navigation
 
Description Detecting the relative position of the docking station is a very important issue for the homing of AUVs (Autonomous Unmanned Vehicles). To detect the position of the light source, a pinhole camera model structure was proposed like the camera model. However, due to the sensor resolution and the distortion errors of the pinhole camera system, the application of the camera of docking the under turbid sea environments is almost impossible.
In this paper, a new method detecting the position of the docking station using a light source is presented. Also, a newly developed optical sensor which makes it much easier to sense the light source than the camera system for homing of the AUV under the water is performed. In addition, to improve the system, a neural network (NN) algorithm constructing a model relating the light inputs and optical sensor which are developed in this study is proposed.
To evaluate the performance of the NN algorithm, the experiments were performed in the air beforehand. The result shows that the NN algorithm with AUV docking system using the NN model is better than the pinhole camera model.
 
Publisher Taiwan Association of Engineering and Technology Innovation
 
Date 2020-01-01
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier http://ojs.imeti.org/index.php/IJETI/article/view/4158
10.46604/ijeti.2020.4158
 
Source International Journal of Engineering and Technology Innovation; Vol 10 No 1 (2020); 15-24
2226-809X
2223-5329
 
Language eng
 
Relation http://ojs.imeti.org/index.php/IJETI/article/view/4158/915
http://ojs.imeti.org/index.php/IJETI/article/view/4158/929
 
Rights Copyright (c) 2019 Thieu Quang Minh Nhat, Hyeung-Sik Choi, Mai The Vu, Joono Sur, Jin-Il Kang, Hyun-Joong Son
http://creativecommons.org/licenses/by-nc/4.0
 

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