Researches on the tender leaf identification and mechanically perceptible plucking finger for high‐quality green tea

BACKGROUND: Intelligent identification and precise plucking are the keys to intelligent tea harvesting robots, which are currently of increasing significance. Aiming at plucking tender leaves for high-quality green tea production, in this study, a tender leaf identification algorithm and a mechanically perceptible plucking finger have been proposed. RESULTS: Based on the segmentation algorithm and color features, the tender leaf identification algorithm shows an average identification accuracy of over 92.8%. The mechanically perceptible plucking finger plucks tender leaves in a way that a human hand does, aiming to maintain the high quality of tea products. Though finite element analysis, we determine the ideal size of grippers and the location of strain gauge attachment on a gripper to enable the employment of feedback control of desired gripping force. As revealed in our experiments, the success rate of tender leaf plucking reaches 92.5%, demonstrating the effectiveness of our design. CONCLUSION: The results show that the tender leaf identification algorithm and the mechanically perceptible plucking finger are effective for identification of tender leaves and plucking, providing a foundation for the development of an intelligent tender leaf plucking robot. © 2024 Society of Chemical Industry.