The harvesting operation for eggplants is complicated and accounts for a little less than 40% of the total number of working hours. For automating the harvesting operation, an intelligent robot that can emulate the judgment of human labor is necessary. This study was conducted with a view to developing a robotic harvesting system that performs recognition, approach, and picking tasks. In order to accomplish these tasks, 3 essential components were developed. First, a machine vision algorithm combining a color segment operation and a vertical dividing operation was developed. The algorithm could detect the fruit even under different light conditions. Next, a visual feedback fuzzy control model to actuate a manipulator was designed. The control model enabled the manipulator end to approach the fruit from a distance of 300 mm. Furthermore, an end-effector composed of a fruit-grasping mechanism, a size-judging mechanism, and a peduncle-cutting mechanism was developed. It produced enough force for grasping the fruit and cutting the tough peduncle. Finally, the 3 essential components were functionally combined, and a basic harvesting experiment was conducted in the laboratory to evaluate the performance of the system. The system showed a successful harvesting rate of 62.5%, although the end-effector cut the peduncle at a slightly higher position from the fruit base. The execution time for harvesting of an eggplant was 64.1 s.

A robotic harvesting system, which emulates the fruit recognition, approach, and picking This study showed the great feasibility of automating the basic harvesting motion for eggplants.

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This study was conducted as a first step in the development of the robotic harvesting system for eggplants.The robotic harvesting system with hand-eye structure was fabricated and the visual feedback fuzzy control model to operate the manipulator was developed.The control model was examined in terms of manipulator guidance to the fruit, estimation of the fruit maximal diameter for selective harvesting and estimation of the fruit angle for the picking movement.From the results of the approach experiment, the control model enabled the manipulator end to reach a fruit 300 mm away with 6 to 10 feedback signals.The manipulator trajectory varied in vertical direction with fruit location and the control model actuated the manipulator end slightly upward than the target region.