Abstract: In order to solve the current agricultural picking robot problem of target recognizing and localizing difficulties, this paper uses an improved YOLOv3 algorithm combined with 3D vision technology to achieve accurate recognition and localization of the target based on the original agricultural picking robot, and completes the transformation between the target coordinate system and the robot coordinate system by calibration. The performance of improved YOLOv3 algorithm is analyzed through experiments, and compared with the previous YOLOv3 algorithm, Fast RCNN algorithm and Faster RCNN algorithm. The research shows that improved YOLOv3 algorithm and 3D vision have higher recognizing accuracy and localizing accuracy, and the recognizing accuracy is increased by 5.5%, 9% and 1.4% respectively, and the maximum localizing errors were reduced by 0.69, 0.44 and 0.28 mm respectively. It can better complete the follow-up picking work, which has important reference value for the development of agricultural robot.