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.