Harvesting is one of the most challenging tasks in fruit production. Robotic
fruit harvesting technologies are being studied because of labor-intensive and costly
handpicking. Due to the unstructured and dynamic characteristics of both the target
fruit and its surrounding environment, current harvesting robots have limited
performance. Therefore, the commercial applications of most fruit harvesting robots
are unrealized. The application and research progress of fruit harvesting robots in apple
and kiwifruit harvesting have been reported in this chapter. The applications and
development of fruit detection and end-effector design for complex orchard are
focused. The main methods used in fruit detection are reviewed, including single
feature detection methods, multi-features fusion detection methods, deep learning
methods, and 3D reconstruction methods. The technology of end-effector design for
selective harvesting with apple and kiwifruit, and shake-and-catch mechanism for bulk
harvesting with apple are also reviewed. Existing research problems of fruit harvesting
robots in robotic harvesting applications are mentioned, and future development
directions of agriculture robots are described.
Keywords: Apple, End-effector, Fruit detection, Kiwifruit, Selective harvesting.
