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In this study, underwater recognition technology and a fuzzy control system were adopted to adjust the attitude and revolution speed of a self-developed autonomous underwater vehicle (AUV). To validate the functionality of visual-recognition control, an experiment was conducted in the towing tank at the Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University. An underwater lighting box was towed by a towing carriage at low speed. By adding real-time contour approximation and a circle-fitting algorithm to the image-processing procedure, the relationship between the AUV and the underwater lighting box was calculated. Both rudder plane angles and propeller revolution speeds were determined after the size and location of the lighting box was measured in the image. Finally, AUV performance with visual-recognition control was verified by controlling the target object in the image center during passage. [ABSTRACT FROM AUTHOR]

In this study, underwater recognition technology and a fuzzy control system were adopted to adjust the attitude and revolution speed of a self-developed autonomous underwater vehicle (AUV). To validate the functionality of visual-recognition control, an experiment was conducted in the towing tank at the Department of Systems and Naval Mechatronic Engineering, National Cheng Kung University. An underwater lighting box was towed by a towing carriage at low speed. By adding real-time contour approximation and a circle-fitting algorithm to the image-processing procedure, the relationship between the AUV and the underwater lighting box was calculated. Both rudder plane angles and propeller revolution speeds were determined after the size and location of the lighting box was measured in the image. Finally, AUV performance with visual-recognition control was verified by controlling the target object in the image center during passage.