Resumen
Autonomous underwater manipulation is very important for the robotic and intelligence operations of oceanic engineering. However, a small target often involves limited features and results in inaccurate visual matching. In order to improve visual measurement accuracy, this paper has proposed an improved unsharp masking algorithm to further enhance the weak texture region of blurred and low contrast images. Moreover, an improved ORB feature-matching method with adaptive threshold, non-maximum suppression and improved random sample consensus has also been proposed. To overcome unknown underwater disturbances and uncertain system parameters in the underwater robotic manipulations, an adaptive non-singular terminal sliding mode controller has been proposed with a quasi-barrier function to suppress the chattering problem and improve grasp accuracy for small target. Oceanic experiments have been conducted to prove the performance of the proposed method.