Object identification and location used by the fruit and vegetable picking robot based on human-decision making

Abstract

The key to a picking robot is to identify and locate accurately in a fruit and vegetable picking site. This paper presented a method that was based on human-decision making. The human-decision making could overcome the difficulties brought by light environment, leaves shading, fruit ripening, fruit overlapping, etc. First, the binocular vision system was applied to obtain close-range pictures of the fruit and vegetable picking site; second, the picking points were chosen by human-decision making; then, the corresponding points of picking points were clicked on the screen based on epipolar geometry; finally, the coordinate transformation was used to calculate the spatial value of the picking points. The simulation experiment of cucumber picking (4 groups, 10 picking points in each group) in lab shown the maximum errors obtained were 15.1mm in vision depth direction and 8.7mm in horizontal direction. Both errors had no regular pattern, which was caused by inaccuracy in pixel when researchers click the picking points. Meanwhile, light condition, whether sunny or cloudy, had little effect on accuracy of identification and location. The research displays that this method can satisfy the need of accurate identification and location of picking points by the robot so it can be applied in design of the fruit and vegetable picking robot, improving the picking robot's quality of simplicity and accuracy in practice.