花序梗(解剖学)
托盘
机器人
人工智能
农业工程
抽吸
机器视觉
任务(项目管理)
模拟
工程类
计算机科学
园艺
计算机视觉
生物
机械工程
系统工程
作者
Shigehiko Hayashi,Kenta Shigematsu,Satoshi Yamamoto,Ken Kobayashi,Yasushi Kohno,Junzo Kamata,Mitsutaka Kurita
标识
DOI:10.1016/j.biosystemseng.2009.09.011
摘要
We developed a strawberry-harvesting robot, consisting of a cylindrical manipulator, end-effector, machine vision unit, storage unit and travelling unit, for application to an elevated substrate culture. The robot was based on the development concepts of night operation, peduncle handling and task sharing with workers, to overcome the robotic harvesting problems identified by previous studies, such as low work efficiency, low success rate, fruit damage, difficulty of detection in unstable illumination and high cost. In functional tests, the machine vision assessments of fruit maturity agreed with human assessments for the Amaotome and Beni-hoppe cultivars, but the performance for Amaotome was significantly better. Moreover, the machine vision unit correctly detected a peduncle of the target fruit at a rate of 60%. In harvesting tests conducted throughout the harvest season on target fruits with a maturity of 80% or more, the successful harvesting rate of the system was 41.3% when fruits were picked using a suction device before cutting the peduncle, while the rate was 34.9% when fruits were picked without suction. There were no significant differences between the two picking methods in terms of unsuccessful picking rates. The execution time for the successful harvest of a single fruit, including the time taken to transfer the harvested fruit to a tray, was 11.5 s.
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