本文選題：小番茄　切入點：腋芽摘除　出處：《浙江大學》2016年博士論文

【摘要】：櫻桃小番茄腋芽摘除是提高產量的關鍵,由于腋芽顏色特征和周圍枝條、葉片相近,且容易被遮擋,本文以小番茄植株為對象,以成功摘除腋芽為目標,研究了圖像采集、去除點定位,側枝水平投影角測量等關鍵問題。主要研究內容與成果：(1)研究了農藝技術,使用半剪的方式摘除櫻桃小番茄的腋芽。測量了定植后的櫻桃小番茄植株幾何特性,還測定了其腋芽、側枝的力學特性,獲得了櫻桃小番茄的株高、主莖直徑、節(jié)距、側枝朝向、傾角等特征參數。提出在溫室大棚中應標準化種植,按照固定的行距、株距、畦距等要求,為機器人自動摘除腋芽提供一定基礎。(2)研制了藍色LED光源染色系統,照射小番茄植株的側枝基部,將其用藍光染色,方便進行圖像分割。建立了藍色LED可調式染色系統,通過光照度傳感器檢測周圍環(huán)境的照度,調節(jié)燈珠的亮度,防止發(fā)生高光反射或者染色不足。對RGB顏色空間的B分量進行圖像分割,得到目標部位清晰完整的圖像。(3)通過快速傅里葉變換(FFT),使用低通濾波器去除毛刺和噪聲,保留基本輪廓特征；由形態(tài)學膨脹算法突出腋芽兩側特征點,通過Shi-Tomasi角點檢測算法,找到目標圖像角點,再經過特征點判別算法,找到特征點,由此判別腋芽存在與否,定位腋芽去除點,最后摘除腋芽。實驗結果表明,腋芽識別的成功率為93.9%,腋芽摘除成功率為88.9%,能滿足自動去除的要求。(4)設計了光電式自動旋轉測向機構。采用閉合環(huán)形機構環(huán)繞櫻桃小番茄主莖,并通過旋轉方式使固定在活動環(huán)上的光電傳感器能水平360。掃描側枝,得到側枝的水平投影方向角。分析活動環(huán)的運動軌跡,得到其線速度與角速度的關系及比例系數。經試驗表明：比例系數為1.5,角速度為1.875π/s,線速度為25mm/s時,檢測成功率為97%,角度標準差為±8.6。。高度補償設定為20mm,成功率為91%。對42株櫻桃小番茄的153個側枝進行測試,在1.8m高度內的成功率為88.2%。(5)標定了工業(yè)攝像頭,標定結果誤差在2mm之內。分析了單目攝像頭測距的不足,使用超聲波測距傳感器與攝像頭組成定位系統,并對超聲波測距傳感器進行標定,根據其相對攝像機坐標系的波束向量。(6)完成了腋芽摘除機器人末端執(zhí)行機構的整體設計和裝配。確定了基于導軌的機械導航方式,并使用二次定位法,使機器人準確定位櫻桃小番茄植株位置。分析了機械臂的正逆運動。進行摘芽整體試驗,總成功率為83%。
[Abstract]:Axillary bud extraction is the key to increase the yield of cherry tomato. Because of the color characteristics of axillary bud and the surrounding branches, the leaves are similar and easily blocked, this paper studies the image collection of the small tomato plant as the object and successfully picking the axillary bud as the target. The main contents and results of this study were as follows: 1) the agronomic technique was studied, and the axillary buds of cherry tomato were removed by semi-cutting. The geometric characteristics of the plants were measured. The results were as follows: (1) the main contents and results were as follows: (1) the agronomic technique was used to remove the axillary buds of the cherry tomato, and the geometric characteristics of the plants were measured. The mechanical properties of axillary bud and lateral branch were also determined, and the plant height, diameter of main stem, pitch, lateral branch orientation and inclination angle of cherry tomato were obtained. The blue LED light source dyeing system was developed to illuminate the lateral branch base of tomato plant and dye it with blue light. A blue LED adjustable dyeing system is established to detect the illumination of the surrounding environment and adjust the brightness of the lamp beads. The B component of the RGB color space is segmented to get a clear and complete image of the target part. FFT3 is used to remove burr and noise through fast Fourier transform (FFT), low pass filter (LPF) is used to remove burr and noise. The morphological expansion algorithm is used to highlight the characteristic points on both sides of the axillary bud, and the corner point of the target image is found by the Shi-Tomasi corner detection algorithm, and then the feature point is found through the feature point discrimination algorithm, and then the axillary bud is judged to exist or not. Location of axillary bud removal point, and finally removal of axillary bud. The successful rate of axillary bud recognition was 93.9, and the successful rate of axillary bud removal was 88.9.The photoelectric automatic rotation direction finding mechanism was designed to meet the requirement of automatic removal. The closed ring mechanism was used to surround the main stem of cherry tomato. And the photoelectric sensor fixed on the active ring can be horizontal 360 by rotation. The horizontal projection direction angle of the lateral branch is obtained by scanning the lateral branch, and the moving track of the active ring is analyzed. The relationship between the linear velocity and the angular velocity and the proportional coefficient are obtained. The experimental results show that the ratio coefficient is 1.5, the angular velocity is 1.875 蟺 / s, and the linear velocity is 25mm/s. The successful rate of detection was 97 and the standard deviation of angle was 鹵8.6.The height compensation was set to 20mm and the success rate was 91. The industrial camera was calibrated by testing 153 branches of 42 cherry tomatoes at a height of 1.8m. The error of calibration results is within 2mm. The shortcomings of monocular camera ranging are analyzed. The ultrasonic ranging sensor and camera are used to form a positioning system, and the ultrasonic ranging sensor is calibrated. According to the beam vector of relative camera coordinate system, the whole design and assembly of the terminal actuator of axillary bud removal robot are completed. The mechanical navigation mode based on guide rail is determined, and the secondary positioning method is used. The robot is able to locate the position of cherry tomato plant accurately. The forward and inverse movement of the robot arm is analyzed. The whole experiment of picking buds shows that the total power is 83%.
【學位授予單位】：浙江大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：S225.92;TP242

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