Research progress of intelligent mechanized tea picking technology and equipment

doi:10.13733/j.jcam.issn.2095-5553.2024.09.046

Abstract

Abstract:

In order to realize intelligent mechanized tea picking，increase production increase，save cost，increase market competitiveness and meet the development needs of digital agriculture and rural areas，the key technologies limiting the development of tea picking machinery and equipment such as end.effector，detection and positioning and picking sequence planning were summarized， and the research status was described and analyzed. The current outstanding research achievements in the field of intelligent mechanized tea picking were summarized. At present，due to the unstructured nature of the tea garden environment，the real.time performance of the end effector was low，the accuracy of the detection and positioning algorithm was greatly affected by nonlinear illumination changes，and the real.time performance of the global optimization of the tea picking sequence planning algorithm was poor. Suggestions were put forward for the development of intelligent mechanized tea picking equipment with low damage and high efficiency， such as the development of cut.collection integrated end.effector，the study of small.target accurate detection algorithm integrating multi.scale features， the design of multi.arm coherent picking sequence planning method， and the promotion of the combination of agricultural machinery and agronomy， so as to provide reference for promoting the research and popularization of intelligent mechanized tea picking equipment in China.

Key words: tea picking robot, end.effector, detection and positioning, picking sequence planning ,

摘要：

为实现茶叶的智能机械化采摘，以增产增量、节约成本、增加市场竞争力、满足数字农业农村的发展需求，围绕末端执行器、检测与定位、采摘顺序规划等限制茶叶采摘机械装备发展的关键技术展开综述，对研究现状进行阐述和分析，总结当前茶叶智能机械化采摘领域突出研究成果。当前受茶园环境的非结构化性影响，茶叶智能机械化采摘存在末端执行器实时性较低、检测与定位算法精度受非线性光照变化影响大、茶叶采摘顺序规划算法的全局寻优实时性较差。对发展低损伤、高效率的智能机械化茶叶采摘装备提出开发剪切—收集一体式末端执行器、研究融合多尺度特征的小目标精准检测算法、设计多机械臂连贯采摘顺序规划方法、推进农机与农艺结合等发展建议。以期为促进我国茶叶智能机械化采摘装备的研究与推广提供参考。

关键词: 茶叶采摘机器人, 末端执行器, 检测定位, 采摘顺序规划

CLC Number:

S225. 93

Wang Minglong, Xu Yao, Zhang Zhihao, Zhu Lixue, Lin Guichao, . Research progress of intelligent mechanized tea picking technology and equipment [J]. Journal of Chinese Agricultural Mechanization, 2024, 45(9): 305-310.

王明龙 , 徐垚 , 张智浩 , 朱立学 , 林桂潮 , . 茶叶智能机械化采摘技术与装备研究进展[J]. 中国农机化学报, 2024, 45(9): 305-310.

References

［1］国家统计局 .中华人民共和国 2023年国民经济和社会发展统计公报［ EB/OL］. https：//www. stats. gov. cn/sj/zxfb/202402/t20240228_1947915. html， 2024-02-28.

［ 2］梅宇，梁晓 . 2023年我国茶叶产销及进出口形势分析［ J］.中国茶叶， 2024，46（4）：18-26.

［ 3］刘仲华，黄建安，龚雨顺，等 .茶叶功能成分的健康作用研究新进展［ J］.中国茶叶， 2021，43（9）：1-11.

［ 4］陆德彪，尹军峰 .我国名优绿茶机械化采摘的意义与实现路径［ J］.中国茶叶， 2018，40（1）：1-4.

［ 5］江超，岳志阳，王贝贝 .计算机智能化技术在农业机械自动化中的应用［ J］.南方农机， 2022，53（24）：67-69.

［ 6］傅隆生，宋珍珍， Zhang Xin，等 .深度学习方法在农业信息中的研究进展与应用现状［ J］.中国农业大学学报， 2020，25（2）：105-120.

Fu Longsheng， Song Zhenzhen， Zhang Xin， et al. Applications and research progress of deep learning in agriculture［J］. Journal of China Agricultural University， 2020，25（2）：105-120.

［ 7］贾江鸣，叶玉泽，程培林，等 .手持式名优茶嫩梢采摘机械手设计与试验优化［ J］.农业机械学报， 2022，53（5）： 86-92.

Jia Jiangming，Ye Yuze，Cheng Peilin，et al. Design and experimental optimization of hand.held manipulator for picking famous tea shoot［J］. Transactions of the Chinese Society for Agricultural Machinery，2022，53（5）：86-92.

［ 8］范元瑞 .并联式自动采茶机的设计与研究［ D］.青岛：青岛科技大学， 2019.

Fan Yuanrui. Design and research of automatictea picking machine basedon parallel robot［D］. Qingdao： Qingdao University of Science and Technology，2019.

［ 9］尚凯歌 .茶叶采摘机器人机械结构设计及控制系统研究［D］.长春：长春理工大学， 2019.

Shang Kaige. Mechanical structure design and control system research of tea.picking robot［D］. Changchun： Changchun University of Science and Technology，2019.

［10］罗坤，吴正敏，曹成茂，等 .茶鲜叶嫩梢捏切组合式采摘器设计与试验［ J］.农业工程学报， 2022，38（13）：1-9.

Luo Kun，Wu Zhengmin，Cao Chengmao，et al. Design and experiment of the combined pinch and cut picker for tea fresh leaf tips［J］. Transactions of the Chinese Society of Agricultural Engineering，2022，38（13）：1-9.

［11］许丽佳，刘琦，代建武，等 .茶叶嫩梢采摘末端执行器的设计研究［ J］.茶叶科学， 2021，41（5）：705-716.

Xu Lijia，Liu Qi，Dai Jianwu，et al. Design of end effector for picking tea shoots［J］. Journal of Tea Science，2021， 41（5）：705-716.

［12］原艳芳 .名优茶采摘机械手与采摘策略研究［ D］.武汉：华中农业大学， 2017.

Yuan Yanfang. Research on the picking manipulator of famous teaand picking strategy［D］. Wuhan： Huazhong Agricultural University，2017.

［13］陈勇，郝淼，潘志刚，等 .茶叶仿生采摘指［ P］.中国专利： CN107006218B，2019-05-21.

［14］郝淼，陈勇，潘志刚，等 .名优绿茶仿生采摘指研制［ J］.食品与机械， 2018，34（10）：86-90.

［15］林桂潮，陈定贤，钟凯勇，等 .基于机器视觉的双机械臂茶叶采摘机器人［ P］.中国专利： CN114731840B，2022-04-07.

［16］吴雪梅，唐仙，张富贵，等 .基于 K-means聚类法的茶叶嫩芽识别研究［J］.中国农机化学报， 2015，36（5）：161-164.

Wu Xuemei，Tang Xian，Zhang Fugui，et al. Tea buds image identification based on lab color model and K-means clustering［J］. Journal of Chinese Agricultural Mechanization，2015，36（5）：161-164.

［17］张可，吕军 .自然条件下茶叶嫩芽图像分割方法的研究［ J］.黑龙江八一农垦大学学报， 2016，28（2）：100-104.

Zhng Ke，Lü Jun. Study on automatic segmentation of tea sprouts under natural conditions［J］. Journal of Heilongjiang Bayi Agricultural University，2016，28（2）：100-104.

［18］Zhang Lei，Zou Lang，Wu Chuanyu，et al. Method of famous tea sprout identification and segmentation based on improved watershed algorithm［J］. Computers and Electronics in Agriculture，2021，184：106108.

［19］韦佳佳 .名优茶机械化采摘中嫩芽识别方法的研究［ D］.南京：南京林业大学， 2012.

Wei Jiajia. Researches on high.quality tea flushes identification for mechanical.plucking［D］. Nanjing： Nanjing Forestry University，2012.

［20］黄海军，吴明晖，王先伟，等 .基于改进分水岭算法的茶叶嫩叶图像识别［ J］.贵州农业科学， 2018，46（4）：136-138.

［21］Tian Jun，Zhu Honglin，Liang Wenjiang，et al. Research on the application of machine vision in tea autonomous picking［J］. Journal of physics Conference Series，2021， 1952（2）：22063.

［22］许高建，张蕴，赖小燚 .基于 Faster R-CNN深度网络的茶叶嫩芽图像识别方法［ J］.光电子·激光， 2020，31（11）：1131-1139. Xu Gaojian， Zhang Yun， Lai Xiaoyi. Recogniti on approaches of tea bud image based on Faster R-CNN depth network［J］. Journal of Optoelectronics·Laser， 2020，31（11）：1131-1139.

［23］Yang Hualin，Chen Long，Chen Miaoting，et al. Tender tea shoots recognition and positioning for picking robot using improved YOLO-v3 model［J］. IEEE Access， 2019，7：180998-181011.

［24］孙肖肖，牟少敏，许永玉，等 .基于深度学习的复杂背景下茶叶嫩芽检测算法［ J］.河北大学学报（自然科学版）， 2019，39（2）：211-216.

Sun Xiaoxiao，Mou Shaomin，Xu Yongyu，et al. Detection algorithm of tea tender buds under complexbackground based on deep learning［J］. Journal of Hebei University（Natural Science），2019，39（2）：211-216.

［25］张晴晴 .基于卷积神经网络的茶树嫩芽识别研究［ D］.合肥：安徽农业大学， 2020.

Zhang Qingqing. Research on tea bud recognition based on convolutional neural network［D］. Hefei： Anhui Agricultural University，2020.

［26］张浩，陈勇，汪巍，等 .基于主动计算机视觉的茶叶采摘定位技术［ J］.农业机械学报， 2014，45（9）：61-65.

Zhang Hao，Chen Yong，Wang Wei，et al. Positioning method for tea picking using active computer vision［J］. Transactions of the Chinese Society for Agricultural Machinery，2014，45（9）：61-65.

［27］龙樟，姜倩，王健，等 .茶叶嫩芽视觉识别与采摘点定位方法研究［ J］.传感器与微系统， 2022，41（2）：39-41.

［28］邹浪 .基于视觉的名优绿茶识别及采摘路径规划［ D］.杭州：浙江理工大学， 2021.

Zou Lang. Identification and picking path planning of famous green tea based on vision［D］. Hangzhou： Zhejiang University of Science and Technology，2021.

［29］姜宏涛，何博侠，章亚非 .采茶机械手嫩芽识别与定位方法研究［ J］.机械与电子， 2021，39（7）：60-64.

Jiang Hongtao，He Boxia，Zhang Yafei. Research on the method of recognizing and positioning the shoots of the tea picking manipulator［J］. Machinery & Electronics，2021， 39（7）：60-64.

［30］王鹏 .并联采茶机器人识别与定位技术研究［ D］.成都：西华大学， 2022.

Wang Peng. Research on identification and positioning technology of parallel tea picking robot［D］. Chengdu： Xihua University，2022.

［31］杨俊成，李淑霞，蔡增玉 .路径规划算法的研究与发展［ J］.控制工程， 2017，24（7）：1473-1480.

［32］吉根林 .遗传算法研究综述［ J］.计算机应用与软件， 2004（2）：69-73.

［33］陈龙 .茶叶嫩芽视觉识别与采摘技术研究［ D］.青岛：青岛科技大学， 2021.

Chen Long. Study on visual recongnition and picking technology of tender tea buds［D］. Qingdao： Qingdao University of Science and Technology，2021.

［34］鲍伟 .基于深度学习的茶叶嫩梢检测及其采摘路径规划［D］.杭州：浙江理工大学， 2021.

Bao Wei. Tea buds detection based on deep learning and its picking path planning［D］. Hangzhou： Zhejiang University of Science and Technology，2021.

［35］李亚涛 .茶叶采摘机器人的视觉检测与定位技术研究［ D］.杭州：浙江理工大学， 2022.

Li Yatao. Research on the visual detection and localization technology of tea harvesting robot［D］. Hangzhou： Zhejiang University of Science and Technology，2022.

［36］Wang Guangjun，Zhao Yi，Wang Zhi. Tea picking path planning based on ant colony algorithm［C］. 2022 41st Chinese Control Conference（CCC）. IEEE， 2022： 1945-1950.

［37］原艳芳，郑相周，林卫国 .名优茶采摘机器人路径规划［ J］.安徽农业大学学报， 2017，44（3）：530-535.

Yuan Yanfang， Zheng Xiangzhou， Lin Weiguo. Path planning of picking robot for famous tea［J］. Journal of Anhui Agricultural University，2017，44（3）：530-535.

［38］汪小名 .茶叶嫩芽信息感知与采摘机理研究［ D］.广州：华南农业大学， 2022.

Wang Xiaoming. Research on tea shoots information perception and harvesting mechanism［D］. Guangzhou： South China Agricultural University，2022.

［39］蔡光跃，董恩清 .遗传算法和蚁群算法在求解 TSP问题上的对比分析［J］.计算机工程与应用， 2007，43（10）：96-98.

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