Vol. 9  No. 3 (2023) · Research Article

Intelligent Positioning of AUV Docking Stations Using Optical Sensing and Neural Network Techniques

Thieu Quang Minh Nhat
Department of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Korea , Korea

Hyeung-Sik Choi
Department of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Korea , Korea

Mai The Vu
Department of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Korea , Korea

Joono Sur
Department of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Korea , Korea

Jin-Il Kang
Department of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Korea , Korea

Hyun-Joong Son
Department of Mechanical Engineering, Korea Maritime and Ocean University, Busan, Korea , Korea

Keywords: optical sensor, neural network, pinhole camera, navigation

Abstract

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.

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