本文選題：小番茄　切入點(diǎn)：腋芽摘除　出處：《浙江大學(xué)》2016年博士論文

【摘要】：櫻桃小番茄腋芽摘除是提高產(chǎn)量的關(guān)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(duì)象,以成功摘除腋芽為目標(biāo),研究了圖像采集、去除點(diǎn)定位,側(cè)枝水平投影角測(cè)量等關(guān)鍵問(wèn)題。主要研究?jī)?nèi)容與成果：(1)研究了農(nóng)藝技術(shù),使用半剪的方式摘除櫻桃小番茄的腋芽。測(cè)量了定植后的櫻桃小番茄植株幾何特性,還測(cè)定了其腋芽、側(cè)枝的力學(xué)特性,獲得了櫻桃小番茄的株高、主莖直徑、節(jié)距、側(cè)枝朝向、傾角等特征參數(shù)。提出在溫室大棚中應(yīng)標(biāo)準(zhǔn)化種植,按照固定的行距、株距、畦距等要求,為機(jī)器人自動(dòng)摘除腋芽提供一定基礎(chǔ)。(2)研制了藍(lán)色LED光源染色系統(tǒng),照射小番茄植株的側(cè)枝基部,將其用藍(lán)光染色,方便進(jìn)行圖像分割。建立了藍(lán)色LED可調(diào)式染色系統(tǒng),通過(guò)光照度傳感器檢測(cè)周圍環(huán)境的照度,調(diào)節(jié)燈珠的亮度,防止發(fā)生高光反射或者染色不足。對(duì)RGB顏色空間的B分量進(jìn)行圖像分割,得到目標(biāo)部位清晰完整的圖像。(3)通過(guò)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(xué)膨脹算法突出腋芽?jī)蓚?cè)特征點(diǎn),通過(guò)Shi-Tomasi角點(diǎn)檢測(cè)算法,找到目標(biāo)圖像角點(diǎn),再經(jīng)過(guò)特征點(diǎn)判別算法,找到特征點(diǎn),由此判別腋芽存在與否,定位腋芽去除點(diǎn),最后摘除腋芽。實(shí)驗(yàn)結(jié)果表明,腋芽識(shí)別的成功率為93.9%,腋芽摘除成功率為88.9%,能滿足自動(dòng)去除的要求。(4)設(shè)計(jì)了光電式自動(dòng)旋轉(zhuǎn)測(cè)向機(jī)構(gòu)。采用閉合環(huán)形機(jī)構(gòu)環(huán)繞櫻桃小番茄主莖,并通過(guò)旋轉(zhuǎn)方式使固定在活動(dòng)環(huán)上的光電傳感器能水平360。掃描側(cè)枝,得到側(cè)枝的水平投影方向角。分析活動(dòng)環(huán)的運(yùn)動(dòng)軌跡,得到其線速度與角速度的關(guān)系及比例系數(shù)。經(jīng)試驗(yàn)表明：比例系數(shù)為1.5,角速度為1.875π/s,線速度為25mm/s時(shí),檢測(cè)成功率為97%,角度標(biāo)準(zhǔn)差為±8.6。。高度補(bǔ)償設(shè)定為20mm,成功率為91%。對(duì)42株櫻桃小番茄的153個(gè)側(cè)枝進(jìn)行測(cè)試,在1.8m高度內(nèi)的成功率為88.2%。(5)標(biāo)定了工業(yè)攝像頭,標(biāo)定結(jié)果誤差在2mm之內(nèi)。分析了單目攝像頭測(cè)距的不足,使用超聲波測(cè)距傳感器與攝像頭組成定位系統(tǒng),并對(duì)超聲波測(cè)距傳感器進(jìn)行標(biāo)定,根據(jù)其相對(duì)攝像機(jī)坐標(biāo)系的波束向量。(6)完成了腋芽摘除機(jī)器人末端執(zhí)行機(jī)構(gòu)的整體設(shè)計(jì)和裝配。確定了基于導(dǎo)軌的機(jī)械導(dǎo)航方式,并使用二次定位法,使機(jī)器人準(zhǔn)確定位櫻桃小番茄植株位置。分析了機(jī)械臂的正逆運(yùn)動(dòng)。進(jìn)行摘芽整體試驗(yàn),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(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：S225.92;TP242

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