Research on Robot Visual Grabbing Based on Mechanism Analysis

This paper mainly studies the problem of grasping objects by manipulator based on vision, and a model-based visual grabbing strategy is proposed. Compared with the existing classical image processing methods including the Sobel operator edge extraction method, the superiority of the corrosion operation edge extraction method used in this strategy has been verified, through several fruit image processing experiments. In order to solve the lack of sufficient number of labeled object recognition samples required by machine learning methods, a model-based image classifier is also established, which is based on artificially extracted object features. Hence, it can be interpreted strongly and does not require training using a large number of data samples. Finally, a visual robot grabbing experiment has been constructed and carried out. The results show that efficiency and accuracy of the image recognition algorithm are proved, and this algorithm is efficient, light and interpretable.