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A Feasibility Study of Applying Laser Line Scanning to AUV Hydrodynamic Parameter Identification

Published online by Cambridge University Press:  30 April 2018

Yu-Cheng Chou ,
Madoka Nakajima  and
Hsin-Hung Chen
Yu-Cheng Chou*
Affiliation:
(Institute of Undersea Technology, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 80424, Taiwan)
Madoka Nakajima
Affiliation:
(Institute of Undersea Technology, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 80424, Taiwan)
Hsin-Hung Chen
Affiliation:
(Institute of Undersea Technology, National Sun Yat-sen University, 70 Lienhai Rd., Kaohsiung 80424, Taiwan)
*
(E-mail: ycchou@mail.nsysu.edu.tw)
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Abstract

Precise control is a key factor in enabling Unmanned Underwater Vehicles (UUVs) to complete various underwater activities. The development of UUV control rules is mostly based on UUV dynamic models. However, such dynamic models contain unknown hydrodynamic parameters that need to be identified. This paper presents a new method, Laser Line Scanning for Hydrodynamic Parameter Identification (LSHPI), which integrates laser line scanning, decoupled dynamics, and evolutionary optimisation to identify the hydrodynamic parameters of an Autonomous Underwater Vehicle (AUV). In this research, laser images, seen from an on board camera's perspective and created using Open Graphics Library (OpenGL), were used to validate LSHPI's feasibility. The accuracy of the AUV positions and Euler angles obtained by the laser image-based methods were investigated for each decoupled One-Dimensional (1D) motion and the influence of other motion disturbances on the accuracy of the obtained AUV positions or Euler angles was also evaluated. In addition, the accuracy of the surge-related hydrodynamic parameters obtained by LSHPI was investigated under different motion disturbances. Based on the hydrodynamic parameter identification results under different motion disturbances, LSHPI's feasibility was successfully validated.

Keywords

Autonomous underwater vehicleHydrodynamic parameter identificationLaser line scanningGenetic algorithm
Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 5 , September 2018 , pp. 1143 - 1160
Copyright
Copyright © The Royal Institute of Navigation 2018 

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