为推动大宗茶机械化采收,提升大宗茶鲜叶采收效率与质量,针对目前仿形采茶机感知传感器易受接触作用力、自然光照或茶蓬面叶片间隙影响,提出了融合2D激光雷达与航向姿态参考系统（Attitude and heading reference system,AHRS）的采茶机割刀仿形距离估计方法,在此基础上,设计并研制精度验证试验台与自动仿形采茶样机,分别开展了室内与田间试验。采茶机采用2D激光雷达测量采茶机割刀仿形距离信息,为提升测距精度与实时性,结合AHRS感知的加速度信息,提出了融合2D激光雷达测距与加速度信息（Fusion of 2D-LiDAR ranging and acceleration,FLRA）的采茶机割刀仿形距离估计算法,并研制了算法精度验证装置和方法,验证了算法有效性。室内试验结果表明,算法处理前仿形距离测距误差均值为36.53 mm,标准差为23.21 mm,算法处理后仿形距离估计误差均值为8.56 mm,标准差为6.31 mm,算法处理后的输出数据延迟更小,提升了仿形距离测距精度与实时性。田间试验表明,鲜叶采收效率达180~210 kg·h-1,割刀覆盖蓬面上鲜叶的平均采收率为92.38%,平均芽叶完整率为85.34%,平均杂质率为4.93%,一芽三叶及以下嫩梢占90.72%,满足大宗茶机采技术标准和后续加工工艺要求,与传统超声波感知的自动仿形采茶机相比,提升了大宗茶鲜叶采收效果。
In order to promote the mechanized harvesting of bulk tea and improve the harvesting efficiency and quality of fresh leaves of bulk tea, a fusion 2D-LiDAR and Attitude and heading reference system（AHRS）was proposed in view of the fact that the sensing sensor of the current profiling tea picker is easily affected by contact force, natural light or the gap between the leaves of the tea canopy. Based on the estimation method of profiling distance of cutting knife of tea picker, an accuracy verification test bench and an automatic profiling tea picker were designed and developed, indoor and field experiments were carried out respectively. The tea picker used 2D-LiDAR to measure the profiling distance at first. In order to improve the ranging accuracy and real-time performance, combined with the acceleration sensed by AHRS, a fusion of 2D-LiDAR ranging and acceleration (FLRA) was proposed. The algorithm accuracy verification platform and method were developed to verify the effectiveness of the algorithm. The indoor test results show that the mean value of the ranging error of the profiling distance before the algorithm processing was 36.53 mm, and the standard deviation was 23.21 mm. After the algorithm processing, the mean value of the profiling distance estimation error was 8.56 mm, and the standard deviation was 6.31 mm, which improved the accuracy and real-time performance of profiling distance ranging. Field tests show that the harvesting efficiency reached 180-210 kg·h-1. The average picking rate of young shoots on the canopy covered by cutter was 92.38%. The integrity rate of bud and leaf was 85.34% and the impurity rate was 4.93%. The young shoots better than one bud and three leaves accounted for 90.72%, which meets the technical standards of bulk tea machine picking and the requirements of subsequent processing technology. Compared with the traditional ultrasonic sensing automatic profiling tea picker, the harvesting effect of bulk tea fresh leaves was improved.
[1] 刘仲华. 中国茶叶深加工产业发展历程与趋势[J]. 茶叶科学, 2019, 39(2): 115-122.
Liu Z H.The development process and trend of Chinese tea comprehensive processing industry[J]. Journal of Tea Science, 2019, 39(2): 115-122.
[2] 易文裕, 程方平, 邱云桥, 等. 单人采茶机研究现状与发展趋势[J]. 中国农机化学报, 2020, 41(11): 33-38.
Yi W Y, Cheng F P, Qiu Y Q, et al.Research status and development trend of single-person tea picking machines[J]. Chinese Journal of Agricultural Machinery, 2020, 41(11): 33-38.
[3] 韩余, 肖宏儒, 秦广明, 等. 国内外采茶机械发展状况研究[J]. 中国农机化学报, 2014, 35(2): 20-24.
Han Y, Xiao H R, Qin G M, et al.Research on the development status of tea picking machinery at home and abroad[J]. Chinese Journal of Agricultural Machinery, 2014, 35(2): 20-24.
[4] Shirai K. Traveling type tea leaf plucking machine: JP2006166710(A) [P].2006-06-29.
[5] 闫晶晶. 仿形采茶机的优化设计及与茶园管理的协调性研究[D]. 合肥: 安徽农业大学, 2019.
Yan J J.Research on the optimal design of the profiling tea picking machine and its coordination with tea garden management [D]. Hefei: Anhui Agricultural University, 2019.
[6] 汤一平, 韩旺明, 胡安国, 等. 基于机器视觉的乘用式智能采茶机设计与试验[J]. 农业机械学报, 2016, 47(7): 15-20.
Tang Y P, Hang W M, Hu A G, et al.Design and experiment of intelligentized tea-plucking machine for human riding based on machine vision[J]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47(7): 15-20.
[7] 赵润茂, 卞贤炳, 陈建能, 等. 分布控制的乘坐式仿形采茶原型机研制与试验[J]. 茶叶科学, 2022, 42(2): 263-276.
Zhao R M, Bian X B, Chen J N, et al.Development and test of a ride-on profiling tea picking prototype machine with distributed control[J]. Journal of Tea Science, 2022, 42(2): 263-276.
[8] 李秋洁, 袁鹏成, 邓贤, 等. 基于移动激光扫描的靶标叶面积计算方法[J]. 农业机械学报, 2020, 51(5): 192-198.
Li Q J, Yuan P C, Deng X, et al.Calculation method of target leaf area based on mobile laser scanning[J]. Journal of Agricultural Machinery, 2020, 51(5): 192-198.
[9] 苗艳龙, 彭程, 高阳, 等. 基于地基激光雷达的玉米株高与茎粗自动测量研究[J]. 农业机械学报, 2021, 52(s1): 43-50.
Miao Y L, Peng C, Gao Y, et al.Research on automatic measurement of maize plant height and stem diameter based on ground-based lidar[J]. Journal of Agricultural Machinery, 2021, 52(s1): 43-50.
[10] 王庆, 车荧璞, 柴宏红, 等. 基于无人机可见光与激光雷达的甜菜株高定量评估[J]. 农业机械学报, 2021, 52(3): 178-184.
Wang Q, Che Y P, Chai H H, et al.Quantitative assessment of sugar beet plant height based on UAV visible light and lidar[J]. Journal of Agricultural Machinery, 2021, 52(3): 178-184.
[11] 陈日强, 李长春, 杨贵军, 等. 无人机机载激光雷达提取果树单木树冠信息[J]. 农业工程学报, 2020, 36(22): 50-59.
Chen R Q, Li C C, Yang G J, et al.Extraction of canopy information of fruit trees by UAV airborne lidar[J]. Chinese Journal of Agricultural Engineering, 2020, 36(22): 50-59.
[12] Kolb A, Barth E, Koch R, et al.Time-of-Flight cameras in computer graphics[J]. Computer Graphics Forum, 2010, 29(1): 141-159.
[13] 吴先坤, 李兵, 王小勇, 等. 单人背负式采茶机的设计分析[J]. 农机化研究, 2017, 39(8): 92-96, 101.
Wu X K, Li B, Wang X Y, et al.Design and analysis of single knapsack tea plucking machine[J]. Journal of Agricultural Mechanization Research, 2017, 39(8): 92-96, 101.
[14] Zhao R M, Hu L, Luo X W, et al.Method for estimating vertical kinematic states of working implements based on laser receivers and accelerometers[J]. Biosystems Engineering, 2021, 203: 9-21.
[15] 韩京清, 王伟. 非线性跟踪-微分器[J]. 系统科学与数学, 1994, 14(2): 177-183.
Han J Q, Wang W.Nonlinear tracking differentiator[J]. System Science and Mathematics, 1994, 14(2): 177-183.
[16] 韩京清, 袁露林. 跟踪-微分器的离散形式[J]. 系统科学与数学, 1997, 19(3): 268-273.
Han J Q, Yuan L L.The discrete tracking differentiator[J]. System Science and Mathematics, 1997, 19(3): 268-273.
[17] 农业部农业机械化管理司. 采茶机作业质量:NY/T 2614—2014 [S]. 北京: [出版者不详], 2014.
Department of Agricultural Mechanization Management of the Ministry of Agriculture. Operation quality of tea picker: NY/T 2614—2014 [S]. Beijing: [n.s.], 2014.
浙公网安备 33019902000101号 
