Picking patterns evaluation for cherry tomato robotic harvesting end-effector design

Picking cherry tomatoes is a time-consuming and labour-intensive task, and robots are an alternative solution to address this issue. The end effector is a key component of the harvesting robot, and it is crucial for achieving automated harvesting of cherry tomatoes. To develop efficient end effectors for picking robots, this study proposes a method to aid end effector design by evaluating and analysing picking patterns of cherry tomatoes. Based on manual picking methods, four potential robot picking patterns are proposed: pressing-breaking combination, pulling, pulling-rotating combination and twisting. A dynamic measurement system based on multi-sensor fusion was developed to measure applied forces and angles during the picking process. Based on the selected picking patterns, two pneumatically controlled picking end effectors, namely, a vacuum end effector and a rotating end effector, were designed. The results of the dynamic measurement experiment and the picking pattern evaluation indicated that the recommended order of picking patterns was twisting, pulling, pulling-rotating combination and pressing-breaking combination in descending order. The picking performance test results of the end effector revealed that for the vacuum end effector, the picking success rate was 66.3 %, whereas the detachment failure was the main reason for picking failure. For the rotating end effector, the picking success rate was 70.1 %, whereas localisation failure and collision were the main reasons for picking failure. This study provides a valuable reference and theoretical analysis basis for the development of cherry tomato picking robots and the design of the end effector in the future.