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Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 33, Number 3(1) (2021)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 907-918
S&M2504 Research Paper of Special Issue https://doi.org/10.18494/SAM.2021.3223 Published: March 5, 2021 Position Control for Underwater Vehicle Using Image Processing [PDF] Chikara Masuzaki, Ikuo Yamamoto, Akihiro Morinaga, Koudai Sadano, Yuto Kai, Tubasa Nakano, and Yuya Kato (Received December 15, 2020; Accepted February 22, 2021) Keywords: underwater vehicle, image processing, PID control, position control
In this paper, we propose a method of position control for an underwater vehicle using a monocular camera. The proposed method does not require an expensive inertial measurement unit (IMU) and uses template matching to track the underwater target and calculate the amount of vehicle movement. The vehicle is then controlled on the basis of the amount of movement. In this paper, we compare the typical similarity calculation methods of template matching, sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC), and investigate which has the greatest accuracy underwater. We also compare proportional (P) control and proportional–integral–derivative (PID) control as vehicle control methods. The results showed that ZNCC was the most accurate in detecting the target and that PID control was about 30% more accurate than P control.
Corresponding author: Chikara Masuzaki  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Chikara Masuzaki, Ikuo Yamamoto, Akihiro Morinaga, Koudai Sadano, Yuto Kai, Tubasa Nakano, and Yuya Kato, Position Control for Underwater Vehicle Using Image Processing , Sens. Mater., Vol. 33, No. 3, 2021, p. 907-918. |
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