The accuracy of target recognition and location is directly related to the picking efficiency, quality and speed of the picking robot. In this article, the research works on target recognition and three-dimensional location of the picking robot in recent years are systematically summarized and analyzed. Several main methods of fruit and vegetable recognition and location are summarized. For target recognition, the methods include digital image processing technology, machine learning image segmentation and classifier and algorithm based on deep learning. For three-dimensional location, the methods consist of monocular color camera, stereo vision matching, depth camera, laser rangefinder and optical 3D camera based on flight time. The main factors that affect the accuracy of fruit and vegetable recognition and positioning are analyzed, which include illumination change, complex natural environment, occlusion and imprecision imaging under dynamic environment interference. Finally, the future development of target recognition and location of picking robot is prospected.