Next Article in Journal
A Study of the Maximum Momentum Flux in the Solitary Wave Run-Up Zone over Back-Reef Slopes Based on a Boussinesq Model
Next Article in Special Issue
Robust Adaptive Heading Control for a Ray-Type Hybrid Underwater Glider with Propellers
Previous Article in Journal
An Investigation into the Suitability of GGBS and OPC as Low Percentage Single-Component Binders for the Stabilisation and Solidification of Harbour Dredge Material Mildly Contaminated with Metals
Previous Article in Special Issue
The Hydrodynamic Noise Suppression of a Scaled Submarine Model by Leading-Edge Serrations
Open AccessArticle

Development of an Image Processing Module for Autonomous Underwater Vehicles through Integration of Visual Recognition with Stereoscopic Image Reconstruction

Department of Systems and Naval Mechatronic Engineering, National Cheng-Kung University, Tainan 70101, Taiwan
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2019, 7(4), 107; https://doi.org/10.3390/jmse7040107
Received: 8 March 2019 / Revised: 12 April 2019 / Accepted: 13 April 2019 / Published: 18 April 2019
(This article belongs to the Special Issue Underwater Technology—Hydrodynamics and Control System)
This study investigated the development of visual recognition and stereoscopic imaging technology, applying them to the construction of an image processing system for autonomous underwater vehicles (AUVs). For the proposed visual recognition technology, a Hough transform was combined with an optical flow algorithm to detect the linear features and movement speeds of dynamic images; the proposed stereoscopic imaging technique employed a Harris corner detector to estimate the distance of the target. A physical AUV was constructed with a wide-angle lens camera and a binocular vision device mounted on the bow to provide image input. Subsequently, a simulation environment was established in Simscape Multibody and used to control the post-driver system of the stern, which contained horizontal and vertical rudder planes as well as the propeller. In static testing at National Cheng Kung University, physical targets were placed in a stability water tank; the study compared the analysis results obtained from various brightness and turbidity conditions in out-of-water and underwater environments. Finally, the dynamic testing results were combined with a fuzzy controller to output the real-time responses of the vehicle regarding the angles, rates of the rudder planes, and the propeller revolution speeds at various distances. View Full-Text
Keywords: autonomous underwater vehicle (AUV); edge detection; fuzzy control; Hough transform; stereo matching autonomous underwater vehicle (AUV); edge detection; fuzzy control; Hough transform; stereo matching
Show Figures

Figure 1

MDPI and ACS Style

Lin, Y.-H.; Chen, S.-Y.; Tsou, C.-H. Development of an Image Processing Module for Autonomous Underwater Vehicles through Integration of Visual Recognition with Stereoscopic Image Reconstruction. J. Mar. Sci. Eng. 2019, 7, 107.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop