【摘要】：相比于傳統(tǒng)的人工施藥和地面機(jī)械施藥,無(wú)人機(jī)植保在便利性、安全性、噴灑效率、節(jié)水節(jié)藥等方面都具有更顯著的效果。近年來(lái),國(guó)內(nèi)植保無(wú)人機(jī)以遙控式多旋翼機(jī)型發(fā)展最快,這種機(jī)型更適合在無(wú)障礙物的空曠地帶進(jìn)行作業(yè);而我國(guó)大片的植保作業(yè)區(qū)域上卻較多地分布著電線桿、樹(shù)木、電力塔甚至房屋等影響無(wú)人機(jī)飛行安全的障礙物,人工遙控式的半自動(dòng)機(jī)型難以滿足這些區(qū)域上的植保作業(yè)需求。國(guó)內(nèi)外相關(guān)企業(yè)和科研機(jī)構(gòu)都在大力研發(fā)更加智能化的植保無(wú)人機(jī)。自動(dòng)避障作為植保無(wú)人機(jī)全自動(dòng)機(jī)型的關(guān)鍵技術(shù)之一具有重要的研究與應(yīng)用價(jià)值。本文的主要工作有:(1)基于激光位移傳感器技術(shù),為植保無(wú)人機(jī)提出一種新的避障檢測(cè)方法。該方法包括數(shù)據(jù)塊提取、障礙物基本參數(shù)計(jì)算以及障礙物模式識(shí)別三個(gè)部分。提出了根據(jù)距離值的有效性,從數(shù)據(jù)序列中提取障礙物所對(duì)應(yīng)的數(shù)據(jù)塊,以平均角度、平均距離和寬度為基本參數(shù)來(lái)描述障礙物,以及基于障礙物的寬度、數(shù)據(jù)塊的最大間隙、跳變次數(shù)和方差為特征的模式識(shí)別分類(lèi)器的設(shè)計(jì)。最后為激光位移傳感器設(shè)計(jì)了一套在FLYING-BOX機(jī)型上的安裝方案,并利用激光位移傳感器、PICO-CV01工控機(jī)和鋰電池設(shè)計(jì)了避障系統(tǒng)的數(shù)據(jù)采集模塊。(2)完成了避障系統(tǒng)的軟件設(shè)計(jì)。將避障軟件劃分為三個(gè)部分即檢測(cè)部分、動(dòng)作部分和異常處理部分。檢測(cè)部分包括飛前自檢、數(shù)據(jù)采集、數(shù)據(jù)處理和模式識(shí)別。提出了根據(jù)俯仰角來(lái)修正檢測(cè)距離,根據(jù)偏航角來(lái)修正檢測(cè)角度的數(shù)據(jù)修正方法。在動(dòng)作部分為無(wú)人機(jī)設(shè)計(jì)了一套避障策略并解釋了避障過(guò)程中動(dòng)作修正的必要性,隨后詳細(xì)分析了影響指令生成的因素和指令產(chǎn)生的過(guò)程。異常處理功能分布在檢測(cè)部分和動(dòng)作部分中,負(fù)責(zé)監(jiān)測(cè)整個(gè)避障系統(tǒng)中各個(gè)子功能的運(yùn)行狀態(tài),一旦某個(gè)或多個(gè)地方出錯(cuò)立刻生成相應(yīng)的錯(cuò)誤編碼并上傳上位機(jī)。上位機(jī)根據(jù)異常情況的不同,采取不同的反應(yīng)。(3)針對(duì)避障檢測(cè)的準(zhǔn)確性和避障系統(tǒng)的有效性進(jìn)行了實(shí)驗(yàn)驗(yàn)證。第一個(gè)實(shí)驗(yàn)驗(yàn)證避障系統(tǒng)對(duì)障礙物角度的檢測(cè)準(zhǔn)確性,第二個(gè)實(shí)驗(yàn)驗(yàn)證避障系統(tǒng)對(duì)于障礙物距離的檢測(cè)準(zhǔn)確性,第三個(gè)實(shí)驗(yàn)驗(yàn)證避障系統(tǒng)對(duì)于樹(shù)木這種類(lèi)型障礙物的檢測(cè)準(zhǔn)確性,包括角度值、距離值的檢測(cè)準(zhǔn)確性以及模式識(shí)別的準(zhǔn)確性,第四個(gè)實(shí)驗(yàn),是室外飛行測(cè)試,驗(yàn)證無(wú)人機(jī)是否能夠按照事先設(shè)計(jì)的避障策略完成對(duì)障礙物的動(dòng)態(tài)繞飛。實(shí)驗(yàn)表明,本文所提的基于激光位移傳感器的避障系統(tǒng)能夠有效地檢測(cè)出未知環(huán)境下障礙物的角度和距離,能夠?qū)χ脖Ｗ鳂I(yè)環(huán)境中典型障礙物做出較為準(zhǔn)確的類(lèi)型判別,并實(shí)現(xiàn)了飛行過(guò)程中的動(dòng)態(tài)避障,驗(yàn)證了本文基于激光位移傳感器的避障系統(tǒng)的有效性。
[Abstract]:Compared with traditional artificial and ground mechanical application, UAV plant protection has more remarkable effects in convenience, safety, spraying efficiency, water saving and pesticide saving. In recent years, the remote-controlled multi-rotorcraft is the fastest developing type of domestic plant protection UAV, which is more suitable to operate in the open area without obstacles. However, in a large area of plant protection in China, there are many obstacles that affect the flight safety of UAVs, such as utility poles, trees, power towers and even houses. The semi-automatic type of artificial remote control is difficult to meet the requirements of plant protection in these areas. Domestic and foreign related enterprises and scientific research institutions are vigorously developing more intelligent plant protection drones. Automatic obstacle avoidance as one of the key technologies of automatic plant protection UAV has important research and application value. The main work of this paper is as follows: (1) based on the laser displacement sensor technology, a new obstacle avoidance detection method for plant protection UAV is proposed. The method includes data block extraction, obstacle basic parameter calculation and obstacle pattern recognition. According to the validity of the distance value, the block corresponding to the obstacle is extracted from the data sequence. The average angle, the average distance and the width are taken as the basic parameters to describe the obstacle, and the maximum gap of the block based on the width of the obstacle. Design of pattern recognition classifier characterized by jump frequency and variance. Finally, a set of installation scheme for the laser displacement sensor is designed on the FLYING-BOX model, and the laser displacement sensor is used. The data acquisition module of obstacle avoidance system is designed by PICO-CV01 industrial computer and lithium battery. (2) the software design of obstacle avoidance system is completed. The obstacle avoidance software is divided into three parts: detection part, action part and exception handling part. The detection part includes pre-flight self-test, data acquisition, data processing and pattern recognition. A data correction method based on pitch angle and yaw angle is proposed. In the part of action, a set of obstacle avoidance strategy is designed for UAV, and the necessity of action correction in obstacle avoidance is explained. Then, the factors that affect instruction generation and the process of instruction generation are analyzed in detail. The exception handling function is distributed in the detection part and the action section, which is responsible for monitoring the running status of each sub-function in the whole obstacle avoidance system. Once one or more places go wrong, the corresponding error codes are generated and uploaded to the host computer. The host computer adopts different reactions according to the abnormal situation. (3) the accuracy of obstacle avoidance detection and the effectiveness of obstacle avoidance system are verified experimentally. The first experiment verifies the accuracy of obstacle avoidance system for obstacle angle detection, and the second experiment verifies the accuracy of obstacle avoidance system for obstacle distance detection. The third experiment verifies the accuracy of obstacle avoidance system for tree obstacle detection, including angle value, distance value and pattern recognition accuracy. The fourth experiment is outdoor flight test. Verify that UAV can complete the dynamic flight of obstacles according to the pre-designed obstacle avoidance strategy. The experimental results show that the obstacle avoidance system based on laser displacement sensor can effectively detect the angle and distance of obstacles in unknown environment, and can make a more accurate classification of typical obstacles in plant protection environment. The dynamic obstacle avoidance in flight is realized, and the effectiveness of the obstacle avoidance system based on laser displacement sensor is verified.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：V279;V249;TP212

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 劉小康;;臨縣MG-1無(wú)人植保機(jī)應(yīng)用情況分析[J];農(nóng)業(yè)技術(shù)與裝備;2016年09期

2 王力群;林朝輝;;基于Arduino UNO平臺(tái)的多適配性無(wú)人機(jī)避障技術(shù)[J];科技創(chuàng)新導(dǎo)報(bào);2016年09期

3 牛祿青;;農(nóng)用無(wú)人機(jī):前景與掣肘[J];新經(jīng)濟(jì)導(dǎo)刊;2016年07期

4 任德元;;淺談我國(guó)農(nóng)業(yè)機(jī)械現(xiàn)狀及發(fā)展趨勢(shì)[J];農(nóng)業(yè)與技術(shù);2016年12期

5 趙國(guó)鋒;;國(guó)外精準(zhǔn)農(nóng)業(yè)發(fā)展及其對(duì)中國(guó)西部地區(qū)的啟示[J];世界農(nóng)業(yè);2016年06期

6 楊雪;;極飛:無(wú)人機(jī)企業(yè)轉(zhuǎn)型植保服務(wù)商[J];農(nóng)經(jīng);2016年06期

7 張穎達(dá);;極飛P20 V2植保無(wú)人機(jī)公開(kāi)亮相[J];農(nóng)機(jī)市場(chǎng);2016年05期

8 蔣智超;劉朝宇;;淺談植保無(wú)人機(jī)發(fā)展現(xiàn)狀及趨勢(shì)[J];新疆農(nóng)機(jī)化;2016年02期

9 王宇;劉泓濱;李華文;;機(jī)器視覺(jué)的災(zāi)后救援機(jī)器人越障系統(tǒng)設(shè)計(jì)[J];傳感器與微系統(tǒng);2016年04期

10 楊晶;張穎達(dá);;極飛農(nóng)業(yè)引領(lǐng)植保無(wú)人機(jī)行業(yè)發(fā)展[J];農(nóng)機(jī)市場(chǎng);2016年04期

相關(guān)碩士學(xué)位論文 前1條

1 王家秀;直升機(jī)載毫米波防撞系統(tǒng)技術(shù)研究[D];南京理工大學(xué);2011年

，

本文編號(hào)：2390591