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農業ロボティクスarXiv:2405.05500

高品質緑茶のための柔らかい葉の識別と機械的知覚摘み指の研究

Research on the Tender Leaf Identification and Mechanically Perceptible Plucking Finger for High-quality Green Tea

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高品質緑茶の若葉を識別するアルゴリズムと、人間の手のように摘み取る力覚フィードバック付き摘み指を開発し、92.8%の識別精度と92.5%の摘み取り成功率を達成した。

著者: Wei Zhang, Yong Chen, Qianqian Wang, Jun Chen

分類: cs.RO, cs.SY, eess.SY

原文アブストラクト

BACKGROUND: Intelligent identification and precise plucking are the keys to intelligent tea harvesting robots, which are of increasing significance nowadays. Aiming at plucking tender leaves for high-quality green tea producing, in this paper, a tender leaf identification algorithm and a mechanically perceptible plucking finger have been proposed. RESULTS: Based on 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 so as to remain 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. Revealed from 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 tender leaves identification and plucking, providing a foundation for the development of an intelligent tender leaf plucking robot.

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