Green Fruit Removal Dynamics for Robotic Green Fruit Thinning End-Effector Development
Green fruit thinning is one of the most important operations in apple production for obtaining high-quality fruit. Manual thinning is time-intensive, making it impractical for large orchards. Some alternative methods, such as chemical and mechanical thinning, have greatly improved work efficiency, but both methods have drawbacks due to non-selective targeting. Robotic green fruit thinning can potentially be as selective as manual thinning. This study developed an effective end-effector for robotic green fruit thinning. Prior to designing the end-effector, a series of fruit removal dynamics tests were conducted to determine the forces required for robotic thinning using pulling or stem-cutting methods on three different apple cultivars. The overall mean forces for pulling detachment were 24.78±0.48 N and 19.91±0.55 N when detaching stem from the fruit-end and the spur-end, respectively. The average force required for stem-cutting was 33.6±8.0 N among the three cultivars. No significant differences were found between the fruit or stem dimensions and the force required for fruit removal. A stem-cutting end-effector prototype was then developed to conduct fruit removal experiments in field conditions. Two end-effector prototype configurations were tested: one placing the end-effector on a handheld bar, and the other integrating the end-effector with a six DoF robotic manipulator. The success rates of green fruit removal for all end-effector prototype experiments were over 90%. The end-effector is a core component of an automated green fruit thinning system. Integration with the robotic manipulator also indicated the potential of a robotic green fruit system to remove fruit at different locations and orientations. A machine vision system will be developed and integrated with the end-effector to develop a robotic green fruit thinning system.
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Work Title | Green Fruit Removal Dynamics for Robotic Green Fruit Thinning End-Effector Development |
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License | In Copyright (Rights Reserved) |
Work Type | Article |
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Publication Date | 2022 |
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Deposited | January 30, 2023 |
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