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
Access
Open Access
Creators
  1. Magni Hussain
  2. Long He
  3. James R Schupp
  4. Paul Heinemann
  5. Paul Heinemann
  6. James Schupp
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Journal of the ASABE
Publication Date January 1, 2022
Publisher Identifier (DOI)
  1. https://doi.org/10.13031/ja.14974
Deposited January 30, 2023

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Version 1
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  • Created
  • Added Green_Fruit_Removal_Dynamics_for_Robotic_Green_Fruit_Thinning_submission_Revision-R2.docx
  • Added Creator Magni Hussain
  • Added Creator Long He
  • Added Creator James R Schupp
  • Added Creator Paul Heinemann
  • Added Creator Paul Heinemann
  • Added Creator James Schupp
  • Published