Human-centered approach for an efficient cucumber harvesting robot system: Harvest ordering, visual servoing, and end-effector

This paper presents a human-centered approach for an efficient cucumber-harvesting robot system. Specifically, harvest ordering, visual servoing, and end-effector-based manipulation functionalities were integrated to realize efficient and stable harvesting. The proposed approach involved determining the optimal harvest ordering, guiding the end-effector to the cucumber pedicel through visual servoing, and designing an end-effector to effectively harvest long cucumbers. The performance of the system was evaluated through preliminary and field experiments. The results of the preliminary experiments showed that harvest ordering decreased the harvesting time and travel length and increased the battery efficiency. The visual servoing was robust, and pedicels could be rapidly detected at a speed of 16–23 FPS through computer vision technologies. The pedicel could be accurately positioned within the cutting area of the end-effector. Furthermore, the proposed end-effector could effectively cut thin cucumber pedicels (3–6 mm), with a 100.0% success rate. Field experiments were conducted at three sites in Korea: Green Monsters, Sangju smart-valley, and Fresh-farm. The harvest success rate at the three sites ranged from 50.9% to 60.0%, with an overall value of 56.6%. The overall average harvest time of 56.0 s. The positional accuracy of the system was within the optimal range of 0–30 mm. Furthermore, the primary causes of harvest failure were analyzed, and future research directions to improve the performance of harvest robots were discussed.