The automated picking technology of tea is an important part of the development of smart agriculture, which affects the development of the tea industry to a certain extent. Tea leaf recognition and robotic tea picking end-effector are the key technologies for automated tea picking. This paper proposes a set of algorithms for tea leaf differentiation and recognition based on the principle of colour difference. And on the basis of this algorithm, a tea picking end-effector is designed. The experiments show that the designed tea picking end-effector has good recognition ability and high tea picking speed.
References
[1]
Mei, Y. and Zhang, S. (2023) Analysis of China’s Tea Production and Domestic Sales in 2022. China Tea, 45, 25-30.
[2]
Zheng, H., Fu, T., Xue, X.L., Ye, Y.X. and Yu, G.H. (2023) Research Status and Prospect of Tea Mechanized Picking Technology. Journal of Chinese Agricultural Mechanization, 44, 28-35.
[3]
Yang, Y.J. (2023) Adhere to Problem Orientation and Promote High-Quality Development of China’s Tea Industry—Current Situation and Suggestions of Tea Industry Development in China. China Tea, 45, 1-5.
[4]
Chen, G.M., Mao, B. and Zhang, Y.N. (2023) Research on Key Technologies of Famous Tea Picking Robot. Journal of Chinese Agricultural Mechanization, 44, 174-179.
[5]
Chen, J.N., Li, H., En, P., Jia, J.M., Zhao, R.M. and Wu, C.Y. (2023) Design and Experiment of Threaded Tube Adsorption Type Famous Tea Harvester. Transactions of the Chinese Society of Agricultural Machinery, 54, 131-139.
[6]
Pan, Z., Gu, J., Wang, W., Fang, X., Xia, Z., Wang, Q., et al. (2024) Picking Point Identification and Localization Method Based on Swin-Transformer for High-Quality Tea. Journal of King Saud University—Computer and Information Sciences, 36, Article ID: 102262. https://doi.org/10.1016/j.jksuci.2024.102262
[7]
Li, H., Kong, M. and Shi, Y. (2024) Tea Bud Detection Model in a Real Picking Environment Based on an Improved Yolov5. Biomimetics, 9, Article 692. https://doi.org/10.3390/biomimetics9110692
[8]
Zhang, F., Sun, H., Xie, S., Dong, C., Li, Y., Xu, Y., et al. (2023) A Tea Bud Segmentation, Detection and Picking Point Localization Based on the MDY7-3PTB Model. Frontiers in Plant Science, 14, Article 1199473. https://doi.org/10.3389/fpls.2023.1199473
[9]
Yu, S.L. (2024) Optimization Design and Experimental Study of Tea-Plucking Machine with Adaptive Adjustment of Cutter. Master’s Thesis, Fujian Agriculture and Forestry University.
[10]
Shen, H.P., Ji, E.C., Ding, W.Q., Deng, J.M., Hua, Y. and Li, T. (2023) Mechanism Design and Dynamic Balance Analysis of 6—DOF Hybrid Robot for Tea-Picking. Transactions of the Chinese Society for Agricultural Machinery, 54, 416-426.
[11]
Chen, J.N., Li, H., Liu, L.M., Jia, J.M., Zhao, R.M. and Wu, C.Y. (2024) Design and Experimental Optimization of End Effector for Picking Famous Tea with Split-Cutter. Transactions of the Chinese Society for Agricultural Machinery, 55, 39-46, 195.
[12]
Zhang, Z.H., Zhu, L.X., Lin, G.C., Zhang, S.A. and Guan, J.X. (2022) Research Progress on Key Technologies of the Famous Tea Picking End Effectors. Modern Agricultural Equipment, 43, 7-12.
