Characterizing apple picking patterns for robotic harvesting

Fruit detachment is one of the essential tasks in apple harvest. The resistance of detaching an apple from the tree is largely influenced by picking patterns. This research aimed at gaining an understanding of fruit detachment process under different picking patterns, focused on characterizing those processes using a few key detaching parameters. It also aimed at identifying an effective robotic picking pattern using a three-finger gripper. To accomplish this goal, one manual and three robotic apple checking patterns were studied, by measuring and analyzing the minimal grasping pressure required to remove a fruit from the tree. The corresponding damage level on removed fruit was also analyzed. The results revealed that manual picking could create a bending moment which helped to reduce the required grasping pressure for fruit detachment, and resulted in no picking-induced fruit bruising on all collected samples. Results obtained from all three robotic picking patterns indicated that the use of a three-finger gripper required higher grasping pressure to detach apples, which resulted in higher percentages of picking-induced fruit bruising. It was found that one of the studied robotic patterns could offer a more manual-like performance than the other two robotic picking patterns. Further investigation assessing potentials and limitations of this identified robotic picking pattern on a more comprehensive scale to gain a deeper understanding of how this pattern works is recommended before it can be used as the base pattern for developing effective and efficient apple picking robots.