Abstract
Underwater target detection technology is an important mean for the development and utilization of marine environment, which has important value in commercial and military fields, and is valued by more and more experts, scholars, and production technicians. A set of behavior-based autonomous underwater vehicle online task planning algorithm is proposed in this article, including the searching behavior based on changing Z-shape, tracking behavior based on an improved artificial potential field theory with likelihood map, rediscovering behavior, and source declare behavior. The proposed algorithm can improve the accuracy and success rate of autonomous underwater vehicle to the source positionficient. The physical experiment results verify the effectiveness of the proposed method.
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