自走連續(xù)振動(dòng)式紅棗收獲機(jī)設(shè)計(jì),連續(xù),振動(dòng),紅棗,收獲,設(shè)計(jì) 塔里木大學(xué) 畢業(yè)論文（設(shè)計(jì)）中期檢查記錄表 2016年 4 月 18 日 學(xué)生姓名 楊海斌 班級(jí) 機(jī)械16-1 課題名稱 自走連續(xù)振動(dòng)式紅棗收獲機(jī) 課題完成進(jìn)度（學(xué)生自述） 第 1 周 查閱相關(guān)文獻(xiàn)，為撰寫開(kāi)題報(bào)告做準(zhǔn)備工作。 第 2-3 周 確定設(shè)計(jì)方案，粗化結(jié)構(gòu)草圖，完成開(kāi)題報(bào)告。 第 4-5 周 根據(jù)工作要求，查閱相關(guān)手冊(cè)書籍，選擇、設(shè)計(jì)計(jì)算同時(shí)校核各零部件。 第6-10周 利用三維設(shè)計(jì)軟件完成各零部件的三維實(shí)體建模。基本完成三維圖的繪制，已開(kāi)始二維裝配圖的繪制。 存在的問(wèn)題及整改措施（學(xué)生自述） 建立的三維模型需要細(xì)節(jié)的修改和補(bǔ)充，沒(méi)有完成規(guī)定的任務(wù)進(jìn)程。需要加快任務(wù)進(jìn)度，盡快完成二維圖的繪制。 指導(dǎo)教師意見(jiàn)（課題進(jìn)展情況、優(yōu)缺點(diǎn)、整改措施等） 指導(dǎo)教師簽名 年 月 日 學(xué)院意見(jiàn) 負(fù)責(zé)人簽名 年 月 日 塔里木大學(xué) 畢業(yè)論文（設(shè)計(jì)）開(kāi)題報(bào)告 課題名稱 自走連續(xù)振動(dòng)式紅棗收獲機(jī) 學(xué)生姓名 楊海斌 學(xué) 號(hào) 8011212125 所屬學(xué)院 機(jī)電院 專 業(yè) 機(jī)械設(shè)計(jì)制造及其自動(dòng)化 班 級(jí) 16-1 指導(dǎo)教師 郭文松 起止時(shí)間 2015-11-27 機(jī)械電氣化工程學(xué)院教務(wù)辦制 填 表 說(shuō) 明 一、學(xué)生撰寫《開(kāi)題報(bào)告》應(yīng)包含的內(nèi)容： 1、本課題來(lái)源及研究的目的和意義； 2、本課題所涉及的問(wèn)題在國(guó)內(nèi)（外）研究現(xiàn)狀及分析； 3、對(duì)課題所涉及的任務(wù)要求及實(shí)現(xiàn)預(yù)期目標(biāo)的可行性分析； 4、本課題需要重點(diǎn)研究的、關(guān)鍵的問(wèn)題及解決的思路； 5、完成本課題所必須的工作條件及解決的辦法； 6、完成本課題的工作方案及進(jìn)度計(jì)劃； 7、主要參考文獻(xiàn)（不少于7篇）。 二、本報(bào)告必須由承擔(dān)畢業(yè)論文（設(shè)計(jì)）課題任務(wù)的學(xué)生在接到“畢業(yè)論文（設(shè)計(jì)）任務(wù)書”的兩周內(nèi)獨(dú)立撰寫完成，并交指導(dǎo)教師審閱。 三、開(kāi)題報(bào)告要求手寫體，字?jǐn)?shù)在3000字以上，由學(xué)生在本報(bào)告冊(cè)內(nèi)填寫，頁(yè)面不夠可自行添加A4紙張。 四、每個(gè)畢業(yè)論文（設(shè)計(jì)）課題須提交開(kāi)題報(bào)告一式三份，一份學(xué)生本人留存，一份指導(dǎo)教師存閱，一份學(xué)生所在學(xué)院存檔，備檢備查。 開(kāi)題報(bào)告正文 1、 本課題來(lái)源及研究的目的和意義： 該課題是指導(dǎo)教師擬定，學(xué)生本人選定的。該課題研究的目的是為了解放生產(chǎn)力，發(fā)展生產(chǎn)力，從而使生產(chǎn)力適應(yīng)生產(chǎn)關(guān)系、經(jīng)濟(jì)基礎(chǔ)適應(yīng)上層建筑，加快我國(guó)的社會(huì)主義建設(shè)貢獻(xiàn)一份力量！該課題研究的意義主要是培養(yǎng)學(xué)生的動(dòng)手和動(dòng)腦能力，使理論知識(shí)與實(shí)踐相結(jié)合，從而獲得直接經(jīng)驗(yàn)，為踏入社會(huì)做好準(zhǔn)備。 棗樹(shù)在我國(guó)的分布很廣，一般來(lái)講，小氣候冬季最低氣溫不低于-32攝氏度，就可以栽培植棗。棗樹(shù)在我國(guó)大面積經(jīng)濟(jì)栽培主要在山東、河北、山西、陜西五省的黃河流域，近年來(lái)安徽、甘肅、湖南、湖北發(fā)展很快。紅棗為溫帶作物，適應(yīng)性強(qiáng)，營(yíng)養(yǎng)豐富，富含鐵元素和維生素。紅棗素有“鐵桿莊稼”之稱，具有耐旱、耐澇的特性，是發(fā)展節(jié)水型林果業(yè)的首選良種。由于經(jīng)濟(jì)的發(fā)展，特色農(nóng)業(yè)的建立，紅棗種植成為現(xiàn)代農(nóng)業(yè)發(fā)展的一條新的產(chǎn)業(yè)項(xiàng)目，紅棗產(chǎn)業(yè)已呈現(xiàn)出區(qū)域化布局、規(guī)?；l(fā)展、多種栽培模式盡顯其效的新模式。各地根據(jù)自己的情況確立了不同的棗樹(shù)種植面積，為農(nóng)民增加了經(jīng)濟(jì)收入。隨著紅棗的種植面積的增加，紅棗的機(jī)械化作業(yè)在紅棗栽培中的重要性逐漸凸顯。依據(jù)最近幾年新疆林果業(yè)發(fā)展的態(tài)勢(shì)分布。新疆果樹(shù)種植每年以10%的速度遞增，由于林果業(yè)的快速發(fā)展，各地正形成了較大的種植規(guī)模，每年收獲季節(jié)需要投入大量的勞動(dòng)力來(lái)完成水果采收?？梢灶A(yù)見(jiàn)到，再過(guò)3~5年，新種植的果樹(shù)進(jìn)去盛果期后，水果采收作業(yè)將會(huì)出現(xiàn)因勞動(dòng)力短缺，采收不及時(shí)，而直接影響果品質(zhì)量和造成大量損失的問(wèn)題。這是因?yàn)?，水果采摘是一?xiàng)勞動(dòng)投入量很大的作業(yè)，有些水果因成熟期不一致，需要多次采摘才能完成收獲;而有些作為鮮食或作為加工用途的果品，因市場(chǎng)對(duì)于果實(shí)外觀要求較高，不能有碰傷、刮傷、壓裂等機(jī)械損傷，采收這些水果時(shí)必須小心翼翼;另外，水果收獲是在離地面3~5米高的空中作業(yè)，以上原因決定了水果采摘是一項(xiàng)費(fèi)時(shí)、費(fèi)工、費(fèi)力的作業(yè)。人工采收水果的速度緩慢，大面積發(fā)展水果種植時(shí)，必須要依靠機(jī)械化來(lái)提高采摘效率。據(jù)有關(guān)資料介紹，有些鮮食水果的采收用工量較大，占水果生產(chǎn)總量用工的50%以上，導(dǎo)致特色果品的生產(chǎn)成本過(guò)大，不能滿足向果品加工企業(yè)提供數(shù)量充足、質(zhì)量?jī)?yōu)越、價(jià)格相對(duì)低廉的原料，這樣極不利于企業(yè)直接參與市場(chǎng)競(jìng)爭(zhēng)。可移式紅棗收獲機(jī)的研究，就是針對(duì)紅棗的采摘時(shí)的要求進(jìn)行設(shè)計(jì)的采摘機(jī)械，紅棗的機(jī)械化收獲對(duì)提高收獲效率，降低收獲作業(yè)成本，做到適時(shí)收獲，減少收獲過(guò)程中造成的機(jī)損失，保證紅棗質(zhì)量，促進(jìn)棗業(yè)生產(chǎn)的規(guī)范化、標(biāo)準(zhǔn)化具有重要現(xiàn)實(shí)意義。 2、 本課題所涉及的問(wèn)題在國(guó)內(nèi)外研究現(xiàn)狀及分析： 由于機(jī)械振動(dòng)式紅棗收獲機(jī)具有結(jié)構(gòu)簡(jiǎn)單，操作方便，作業(yè)可靠，適用范圍廣和通用性好等特點(diǎn)，因此具有廣闊的推廣應(yīng)用前景。近幾年來(lái)，由于新疆特色紅棗種植模式的調(diào)整，矮化值方式將成為部分林果的主要種植方式，因此機(jī)械振動(dòng)式紅棗收獲機(jī)將成為今后機(jī)械采收的一個(gè)新的有待解決的問(wèn)題和關(guān)鍵影響因素的基礎(chǔ)研究。 國(guó)外對(duì)水果機(jī)械化收獲技術(shù)的研究較多，機(jī)械采摘在美國(guó)、西班牙、俄羅斯、意大利、英國(guó)、德國(guó)、丹麥、匈牙利等國(guó)家的果園應(yīng)用較為普遍。目前，機(jī)械采摘量較大的作物有蘋果、葡萄、甜橙、桃、李、杏、櫻桃、油橄欖、核桃、扁桃等。他們采用的機(jī)械收獲方法主要有:震搖法、梳刷法、撞擊法、水力法、半機(jī)械化采收等方法。但是，針對(duì)紅棗收獲的采摘機(jī)械比較少。據(jù)了解，美國(guó)的堅(jiān)果收獲已全部實(shí)現(xiàn)機(jī)械化，美國(guó)的葡萄、柑桔類水果的機(jī)械化收獲問(wèn)題也解決的較好。意大利生產(chǎn)一種鮮食水果收獲機(jī)，專門用于蘋果、梨、杏、李子等鮮食水果的操作，水果收獲的效率可大大提高。同時(shí)也能避免和減少水果在收獲過(guò)程中的機(jī)械損傷。除了收獲機(jī)械之外，還需要引進(jìn)適于機(jī)械化收獲的品種和果園修剪等管理技術(shù)。例如，在法國(guó)和意大利，為實(shí)現(xiàn)水果作業(yè)機(jī)械化，把葡萄樹(shù)普遍栽成扁平形，并花了很大的力量栽培修剪。栽果樹(shù)時(shí)，樹(shù)與樹(shù)排行成列，既有較好的光照與通風(fēng)，又便于拖拉機(jī)進(jìn)去行間松土、施肥、噴藥和采摘。法國(guó)的勃拉特研所據(jù)此設(shè)計(jì)制造了一種高架式葡萄收獲機(jī)，成功地解決了釀酒用葡萄的收獲問(wèn)題。國(guó)外有很多發(fā)展水果機(jī)械化收獲的經(jīng)驗(yàn)，值得我們學(xué)習(xí)和研究。 總之，國(guó)外的水果收獲機(jī)械研究主要在鮮食水果的收獲中，他們是著眼于市場(chǎng)針對(duì)性的研制各種收獲機(jī)械。他們不光強(qiáng)調(diào)機(jī)械一定要適應(yīng)當(dāng)?shù)剞r(nóng)園藝的要求，而且從生物學(xué)角度、農(nóng)園藝角度加大科研力度，并開(kāi)發(fā)利于機(jī)械化作業(yè)的新品種、新農(nóng)園藝等，為機(jī)械化作業(yè)創(chuàng)造條件。這樣就提高了水果的機(jī)械化采收作業(yè)率。 我們國(guó)家雖然紅棗的種類很多，種植面積大，但是對(duì)于機(jī)械化采摘紅棗的技術(shù)還是比較少，機(jī)械化作業(yè)水平很低。近年來(lái)，作為鮮食上市的水果收獲仍沒(méi)有完全實(shí)現(xiàn)機(jī)械化。這是因?yàn)殚L(zhǎng)在果樹(shù)上的果實(shí)的生長(zhǎng)形態(tài)不適于機(jī)械化采摘，而市場(chǎng)對(duì)于商品果外觀要求又較高，不能有碰傷、擦傷等機(jī)械損傷的緣故。雖然這種水果收獲機(jī)需要人工輔助摘果，但摘下后水果的輸送、裝箱等過(guò)程全部是機(jī)械化操作，水果收獲的效率可大大提高，同時(shí)也能避免和減少水果再收獲過(guò)程中的機(jī)械損傷。根據(jù)全國(guó)各地調(diào)查資料顯示，目前我國(guó)的水果機(jī)械還是只停留在節(jié)水灌溉、滴灌、施肥一體化，包裝保鮮等有限的幾個(gè)工序上，在清洗、分級(jí)中偶有使用，而水果采摘機(jī)械還是很少。我國(guó)的水果采摘機(jī)械種類很少，大型的機(jī)械化設(shè)備使用率很低，只有少量的半自動(dòng)機(jī)械在使用。比如，可移動(dòng)水果采摘梯、可伸縮式高枝采果器這樣的改進(jìn)型機(jī)械。這些機(jī)械雖然在某種意義上使生產(chǎn)效率提升，提高了水果的采摘質(zhì)量。但是對(duì)于大面積的果樹(shù)收獲還是不能滿足要求，像紅棗這樣的果實(shí)數(shù)量多，結(jié)果時(shí)，紅棗分布在果樹(shù)的各個(gè)部位，所以如果要提高生產(chǎn)率就需要機(jī)械化程度比較高的水果采摘機(jī)械來(lái)完成。 目前，我國(guó)紅棗收獲主要靠人工手摘和借助簡(jiǎn)單工具輔助，如云梯和采果刀等紅棗，勞動(dòng)強(qiáng)度較大，用工量很多。采收整體技術(shù)水平較低，在操作上都為手動(dòng)控制。采收機(jī)械的研究在我國(guó)仍處于起步階段，尚未見(jiàn)成熟先進(jìn)的實(shí)用機(jī)具報(bào)道。 當(dāng)前,機(jī)械采收的方法主要有振搖法和梳刷法。其中,振搖法是應(yīng)用最多的一種方法, 適用于采收大多數(shù)干果、堅(jiān)果和部分鮮食水果；而梳刷法適用于采收草莓、葡萄等漿果。新疆兵團(tuán)應(yīng)根據(jù)林果生產(chǎn)實(shí)際,從易于實(shí)現(xiàn)機(jī)械采收的紅棗、核桃等特色干果的收獲入手, 研發(fā)基于振搖原理的干果收獲機(jī)具。 新疆農(nóng)墾科學(xué)院農(nóng)機(jī)研究所已首次從意大利引進(jìn)了一臺(tái)干果收獲機(jī)成套設(shè)備, 并于2007年9 月在新疆哈密農(nóng)十三師火箭農(nóng)場(chǎng)進(jìn)行了紅棗、核桃機(jī)械采收的適應(yīng)性試驗(yàn), 效果較好。 自2008年開(kāi)始，新疆農(nóng)墾科學(xué)院機(jī)械裝備研究所經(jīng)過(guò)反復(fù)研究，終于成功研制出了“4YS-24紅棗收獲機(jī)”。該紅棗收獲機(jī)每小時(shí)可采摘50棵棗樹(shù)，采凈率達(dá)到91.5% ，工效提高了10倍左右，而人工采摘紅棗每小時(shí)只能采摘5棵棗樹(shù)。 總的來(lái)說(shuō),新疆兵團(tuán)以及國(guó)內(nèi)林果業(yè)機(jī)械化發(fā)展步伐緩慢,林果業(yè)生產(chǎn)過(guò)程機(jī)械化作業(yè)大部分尚處于空白階段。 3、 對(duì)課題所涉及的任務(wù)要求及實(shí)現(xiàn)預(yù)期目標(biāo)的可行性分析： 設(shè)計(jì)要求一種自走連續(xù)振動(dòng)式紅棗收獲機(jī)包括裝有行心輪的機(jī)架以及分機(jī)，還有鉗式振動(dòng)頭。其特征是:在機(jī)架上放置一個(gè)盛果箱，在盛果箱的前端上部安裝一根吸氣管，所說(shuō)的風(fēng)機(jī)安裝在吸氣管上，吸氣管的自由端口連接著一個(gè)紅棗撿拾吸頭，在盛果箱后部上方的輕雜物沉降室的下端連接這一個(gè)過(guò)濾網(wǎng)兜，在盛果箱中部頂端設(shè)計(jì)一個(gè)豎直向下延伸的擋棗部，擋棗部的長(zhǎng)度與盛果筐的寬度相同。在擋棗部下方的盛果箱內(nèi)放置一個(gè)盛果筐，盛果筐的前端頂部與盛果箱的前臂之間設(shè)計(jì)一個(gè)傾斜的紅棗下滑板。為了實(shí)用的方便在風(fēng)機(jī)和紅棗撿拾頭直接設(shè)計(jì)一根波紋管。而且盛果筐四周壁上均設(shè)置著網(wǎng)孔，擋棗部為平直的擋板，所說(shuō)的紅棗下滑板為柵欄板上的縫隙寬度必須比紅棗的直徑小。 （1）選擇合適配套動(dòng)力，設(shè)計(jì)工作裝置、收集除雜裝置和行走裝置。 （2）運(yùn)用AutoCAD繪制二維裝配圖和零件圖。 （3）利用Solidworks繪制三維圖。 4、 本課題需要重點(diǎn)研究的、關(guān)鍵的問(wèn)題及解決的思路： 本設(shè)計(jì)需要重點(diǎn)研究的是紅棗采摘機(jī)械的基本形式、傳動(dòng)機(jī)構(gòu)、采摘的類型。需要充分發(fā)揮機(jī)械的特性，最大限度的利用機(jī)械結(jié)構(gòu)對(duì)紅棗進(jìn)行采摘并且保證收獲的紅棗質(zhì)量和采凈率。機(jī)械化收獲是整個(gè)生產(chǎn)環(huán)節(jié)里的重要部分，所以研究紅棗采摘機(jī)的技術(shù)具有很重要的意義。 機(jī)械振動(dòng)式紅棗收獲機(jī)工作原理是基于機(jī)械振動(dòng)的果實(shí)脫落原理，主要過(guò)程是通過(guò)操作液壓控制閥控制五個(gè)液壓油缸動(dòng)作。首先，將果樹(shù)振搖裝置的鉗式振動(dòng)頭夾持樹(shù)干；然后，由拖拉機(jī)輸出軸PTO傳遞動(dòng)力經(jīng)由液壓控制回路到鉗式振動(dòng)頭振動(dòng)；振動(dòng)頭產(chǎn)生的機(jī)械振動(dòng)傳遞給果樹(shù)；果枝在接受了外加的強(qiáng)迫振動(dòng)后，也以一定的頻率和振幅振動(dòng)，從而就使果枝上的果實(shí)以某種形式的振動(dòng)而加速運(yùn)動(dòng)；加速運(yùn)動(dòng)的物體要受到慣性力的作用，當(dāng)慣性力大于果實(shí)與果枝的結(jié)合力時(shí)，果實(shí)就會(huì)掉落。實(shí)驗(yàn)結(jié)果表明：樹(shù)干的振動(dòng)是一種無(wú)限多自由度的懸臂梁橫向振動(dòng)，其一階基頻的計(jì)算機(jī)值和實(shí)驗(yàn)值相差在10%左右。 5、 完成本課題所必須的工作條件及解決的辦法： 塔里木大學(xué)位于南疆中心位置，區(qū)域優(yōu)勢(shì)明顯。新疆生產(chǎn)建設(shè)兵團(tuán)紅棗種植面積有90萬(wàn)畝，為設(shè)計(jì)開(kāi)展提供了便利的外部條件。塔里木大學(xué)有良好的硬件與軟件設(shè)施，這些都為課題的實(shí)施提供了保障。 機(jī)械振動(dòng)式紅棗收獲機(jī)適用于樹(shù)冠較大，樹(shù)干直徑較粗且操作空間較大的稀疏果園，而且要求棗樹(shù)長(zhǎng)得筆直，不能有太大的彎曲度和根部不能有太多的分叉。設(shè)計(jì)要注意的是：采摘的方式；采摘后果實(shí)如何利于采集；保證對(duì)果實(shí)的損傷不影響其質(zhì)量；使用簡(jiǎn)便的采摘方式；減少對(duì)果實(shí)的打擊；提高采集裝置承接的效率；傳動(dòng)裝置要配套和采摘機(jī)械相互協(xié)調(diào)。經(jīng)過(guò)查詢資料和實(shí)際的測(cè)量，確定收獲機(jī)所具備的基本條件是：工作寬度小，易移動(dòng)，采摘過(guò)程對(duì)果實(shí)的損傷小。經(jīng)研究采用負(fù)壓撿拾，正壓傳送，中間擋棗部前設(shè)計(jì)成弧形進(jìn)一步降低紅棗與擋棗部進(jìn)行碰撞時(shí)出現(xiàn)的碰撞摩擦力，減少紅棗表皮的損傷。紅棗擋部也可以設(shè)計(jì)成一塊平直的擋板，可以減少制作的成本。 6、 完成本課題的工作方案及進(jìn)度計(jì)劃： 第1～2周 查閱相關(guān)文獻(xiàn)，撰寫開(kāi)題報(bào)告。 第3～4周 根據(jù)國(guó)內(nèi)外現(xiàn)有的紅棗收獲機(jī)確定棒桿式紅棗收獲裝置的總體設(shè)計(jì)方案，繪制總體結(jié)構(gòu)簡(jiǎn)圖。 第5～6周 根據(jù)工作要求，計(jì)算并查閱相關(guān)手冊(cè)，選擇和設(shè)計(jì)各零部件。 第7～9周 運(yùn)用AutoCAD軟件，繪制二維零件圖和裝配圖。 第10～11周 運(yùn)用三維設(shè)計(jì)軟件完成整機(jī)各零部件的三維建模并進(jìn)行運(yùn)動(dòng)仿真。 第12周 從工藝性能，經(jīng)濟(jì)性能，實(shí)用性能等方面對(duì)產(chǎn)品進(jìn)行綜合評(píng)價(jià)、校核、修正。 第13周 完成設(shè)計(jì)說(shuō)明書。 第14周 整理材料，準(zhǔn)備答辯 工作方案為首先根據(jù)工況選擇原動(dòng)力部分即發(fā)動(dòng)機(jī)的型號(hào)，再通過(guò)實(shí)地測(cè)量棗樹(shù)之間的行距和間距初步確定機(jī)器外廓尺寸，然后根據(jù)工作條件設(shè)計(jì)各部分零、部件，如收獲機(jī)機(jī)架的設(shè)計(jì)、底板的設(shè)計(jì)、擋棗部的設(shè)計(jì)，鏈?zhǔn)捷斔蛶У脑O(shè)計(jì)、鉗式振動(dòng)頭的設(shè)計(jì)等等。 7、 主要參考文獻(xiàn)： (1)《機(jī)械設(shè)計(jì)課程設(shè)計(jì)手冊(cè)》（第4版）吳宗澤、羅圣國(guó)等著 高等教育出版社 (2)《機(jī)械設(shè)計(jì)》（第七版）濮良貴、紀(jì)名剛等著 高等教育出版社 (3)《機(jī)械原理》（第七版）陳作模、葛文杰等著 高等教育出版社 (4) <<機(jī)械設(shè)計(jì)手冊(cè)》（第二版）上冊(cè).化學(xué)工業(yè)出版社，1983 (5)《機(jī)械設(shè)計(jì)手冊(cè)》（第二版）中冊(cè).化學(xué)工業(yè)出版社，1983 （6）《機(jī)械設(shè)計(jì)圖冊(cè)》化學(xué)工業(yè)出版社，2002 （7）《農(nóng)業(yè)機(jī)械學(xué)》(第二版)農(nóng)業(yè)出版社，1994 學(xué)生簽名 楊海斌 2015 年 11 月 29 日 指導(dǎo)教師審閱意見(jiàn) 指導(dǎo)教師簽名 年 月 日 Research PaperDesign and control of an apple harvesting robotZhao De-An, Lv Jidong, Ji Wei*, Zhang Ying, Chen YuSchool of Electrical and Information Engineering, Jiangsu University, XueFu Road No.301, Zhenjiang, Jiangsu Province 212013, PR Chinaa r t i c l e i n f oArticle history:Received 9 February 2011Received in revised form4 July 2011Accepted 17 July 2011Published online 6 August 2011A robotic device consisting of a manipulator, end-effector and image-based vision servocontrol system was developed for harvesting apple. The manipulator with 5 DOF PRRRPstructure was geometrically optimised to provide quasi-linear behaviour and to simplify thecontrol strategy. The spoon-shaped end-effector with the pneumatic actuated gripper wasdesigned to satisfy the requirements for harvesting apple. The harvesting robot autono-mouslyperformeditsharvestingtaskusingavision-basedmodule.Byusingasupportvectormachine with radial basis function, the fruit recognition algorithm was developed to detectand locate the apple in the trees automatically. The control system, including industrialcomputer and AC servo driver, conducted the manipulator and the end-effector as itapproached and picked the apples. The effectiveness of the prototype robot device wasconfirmed by laboratory tests and field experiments in an open field. The success rate ofappleharvestingwas77%,andtheaverageharvestingtimewasapproximately15sperapple.Crown Copyright 2011 Published by Elsevier Ltd on behalf of IAgrE. All rights reserved.1.IntroductionIn China, with the rapid development of the rural economyand the continuous adjustment of planting structures, fruitcultivation areas, such as apple, citrus and pear, havereached 8-9 million ha since 1993, accounting for one-quarterof the total fruit cultivation area in the world. However, fruitharvesting tasks, which take 50%e70% of the total workinghours, still depend on manual labour (Xu & Zhang, 2004.Harvesting is expected to be automated because the farmingpopulation is gradually decreasing in China. In addition,since the fruit trees are tall, harvesting work has to be con-ducted using step ladders, which makes manual harvestingdangerous and inefficient. Therefore, there is a strong desireto mechanise and automate harvesting. Mechanical har-vestingexperimentshavebeenperformedontheassumptionof once-over harvesting in some areas, but exploitation ofthis strategy is not yet widespread (Hancock, 1999). Selectiveharvesting, which is commonly used, requires sophisticatedrobotic technology. In short, it is necessary to design anintelligent robot with human-like perceptive capabilities. Forinstance, the machine needs to detect fruit, calculate theposition of the fruit and then pick it without damaging thepericarp or the fruit tree.Research on fruit harvesting robots took place in the 1980s.Kawamura, Namikawa, Fujiura, and Ura (1984) first developeda fruit-harvesting robot for orchards. Later, Grand, Rabatel,Pellenc, Journeau, and Aldon (1987), developed an apple-harvesting robot. Since then, their pioneering studies werefollowed by many research papers covering several aspects(e.g., ;Edan, Rogozin, Flash, & Miles, 2000; Foglia & Reina, 2006;Hwang&Kim,2003;Kondo&Ting,1998;Muscato,Prestifilippo, Abbate, & Ivan, 2005; Sakai, Osuka, Maekawa, &Umeda, 2007, 2008; Sarig, 1993; Van Henten, Hemming, VanTuijl, Kornet, Meuleman, 2002). In addition, several relevantstudiesonagriculturalrobotsingreenhouseshavebeencarried* Corresponding author. Tel.: 86 511 82028322; fax: 86 511 82028322.E-mail address: (J. Wei).Available at journal homepage: engineering 110 (2011) 112e1221537-5110/$ e see front matter Crown Copyright 2011 Published by Elsevier Ltd on behalf of IAgrE. All rights reserved.doi:10.1016/j.biosystemseng.2011.07.005out; for instance, tomato harvesting (Monta et al., 1998),cucumber harvesting (Van Henten, Van Tuijl, Hemming,Kornet,Bontsema&VanOs,2003),cherryharvesting(Tanigaki, Fujiura, Akase, & Imagawa, 2008), strawberry har-vesting (Hayashi et al., 2010). However, most of the fruit har-vesting robots discussed in the literature are not currentlymanufacturedorsold.Instead,theyremainintheresearchanddevelopment stages. To this end, it is important to supportfurtherresearch anddevelopment toimprove the performanceand reduce the initial set-up costs of these robots.Based on the concepts above, this study intends to developand evaluate a competitive low price device for automaticharvesting, i.e., an apple-harvesting robot. Firstly, a detaileddescription on the components of the robot including themanipulator,theend-effectorandtheimage-basedvisionservocontrol system is described. Secondly, the geometrically opti-misation of the manipulator to gain a quasi-linear behaviourand simplify the control strategy is described. Thirdly, the end-effectorwiththepneumaticactuatedgripperdesignedtosatisfythe requirements for harvesting apple is described. Based onthis design, the harvesting robot autonomously performs itsharvesting task using a vision-based module to detect andlocate the apple in the trees, and control system conducts themanipulator and the end-effector to approach and pick apple.To verify the validity of the developed harvesting robot, thelaboratory tests and field experiments in an open field wereperformed. The experimental results are the important contri-bution of this paper.The paper is organised as follows: in section 2 the maincomponents of the robot are presented in detail, i.e., themanipulator, the end-effector and the image-based visionservo control system, respectively; in section 3 the experi-mental results are discussed to show the feasibility of therobot system proposed; finally, in section 4 conclusions aredrawn and suggestions for future research are made.2.Material and methods2.1.Mechanical structure of apple harvesting robotA prototype model of the apple harvesting robot is designedfor both efficiency and cost effectiveness. It mainly consists ofan autonomous vehicle, a 5 degree of freedom (DOF) manip-ulator, an end-effector, the sensors, the vision system andcontrol system. The mechanical structure of fruit harvestingrobot self-developed in this paper is shown in Fig. 1.2.1.1.The autonomous mobile vehicleA crawler type mobile platform was selected as the mobilevehicle. It carried the power supplies, pneumatic pump,electronic hardware for data acquisition and control, and themanipulator with the end-effector for cutting the fruit. Globalposition system (GPS) technology was used for autonomousnavigation of the mobile vehicle, whose typical speed was1.5 ms?1.2.1.2.The manipulatorCompared with other structures, as described in Sakai,Michihisa, Osuka, and Umeda (2008), joint structure is effec-tive for any position and orientation in three-dimensionalspace. The operation of a harvesting robot is a random largespace distribution, where a lot of obstacles may exist aroundthe robot. A joint manipulator with multi-degrees of freedomhas an arbitrary curve fitting function. It is therefore easy toavoid obstacles by operating the corresponding joints whenthe end-effector reaches the object position. Therefore,aharvestingrobotmanipulatorwith5DOFprismatic-revolute-revolute-revolute-prismatic (PRRRP) structure to bemounted on autonomous mobile vehicle was designed. Thefirst DOF was used for uplifting the whole manipulator. TheNomenclatureSymbolsCR, CRU, CU, CLU, CLAvoidance sensors numberXc, Yc, ZcThe camera coordinates axesXo, Yo, ZoRobot coordinates axesL1, L2, L3Lengths of waist, major arm and minor armq1;q2;q3Joint angles of waist, major arm and minor arm.u, vImage plane coordinates horizontal and verticalaxesuo, voImage centre coordinatexg, ygProjection centre coordinate of target fruitex, eyThe difference of target fruit image featurebetween xg, ygand uo, voM ? NImage plane pixels of video camerajexmaxj;jeymaxj Maximum of ex and eyDq1; Dq2; Dq3Joint deviationangles of waist, major armandminor armk1, k2Control parameters of armsDd The angle to adjust for the movement of a pixel withunit of degree per pixel.AbbreviationsACAlternating CurrentA/DAnalog, DigitalCCDCharge Coupled DevicesD/ADigital, AnalogDCDirect Current.DOFDegree of FreedomGPSGlobal Position SystemHISHue, Intensity, SaturationIBVSImage-Based Vision ServoPBVSPosition-Based Vision ServoPRRRPPrismatic Revolute Revolute Revolute PrismaticRBFRadial Basis FunctionRSTRotation Scale, TranslationSVMSupport Vector MachineUSBUniversal Serial BusVFWVideo for Windowsbiosystems engineering 110 (2011) 112e122113middle three DOF were for rotation, among which, the seconddriving arm was designed to rotate around the waist, and thethird and fourth ones were rotation axes to move the terminaloperator up and down. This DOF allowed the end-effector tomove towards an arbitrary direction in the work space. Thefifth, and last, DOF was flexible and used for elongation, whichmade the end-effector reach the target location according tothe robot control commands, thus achieving the harvesting offruit (Zhao, Zhao, & Ji, 2009; Zhao, Zhao, & Shen, 2009). Thediscussion above shows that 5 DOF manipulator designedshould be sufficient to perform the harvest operation. Themechanical structure of the manipulator is shown in Fig. 2.The lifting of manipulator was performed by the pump-driven lifting platform, which was able to cope with thespecial circumstances of tall fruit crops. The rotary joints andflexible joints were driven by servo motors. Motion parame-ters of the robot manipulator mechanical structure are shownin Table 1.2.1.3.The end-effectorThe mechanism of end-effector is determined by operationand biological characteristics of the target object. The opera-tion objects of harvesting robot are mainly spherical fruit suchas apple. A spoon-shaped end-effector (shown in Fig. 3) isdesigned according to biological characteristics of sphericalfruit, which are picked by means of cutting off the stalk.The end-effector contained the following parts: a gripper tograsp the fruit and an electric cutting device to separate thefruit from the stalk. The opening and closing of end-effectorgripper was determined by some pneumatic devices, whosequick action, fast response characteristics were suitable forthe switching control of the end-effector. Pressure trans-mission was a transferring mode using compressed gaspressure to achieve energy transference. The apple stalk wassevered by an electric cutter installed in the side of grippermechanism. When the fruit was grasped, the direct current(DC) motors transmited power by flexible wire to drive thecutter rotating around the gripper,cutting off the stalk in frontof end-effector at any position.Fig. 1 e Schematic diagram of the fruit harvesting robot.Fig. 2 e Photograph of the manipulator.biosystems engineering 110 (2011) 112e1221142.2.The sensorsThe non-structural and uncertain features of the operatingenvironment, and the individual differences and randomnature of the operating objects, determines that fruit har-vesting robots should have intelligent sensibility to theircomplex environment (Edan et al., 2000; Zhao, Zhao, & Ji, 2009;Zhao, Zhao, & Shen, 2009). During the process of clamping thefruit, the biological characteristics of fruit including its thinand fragile pericarp put a high demand on grasping force ofend-effector (Monta, 1998). It required sensors to control thegrasping force accurately. In addition, the rotation of arm, itstraveling position and accurate capture also required thesensors to detect and locate fruit (Jiang, Cai, & Liu, 2005; Qiao,Wu, & Zhu, 1999). Furthermore, in order to avoid damagingequipment, causing injury and failing to pick fruit, collisionavoidance of the arm also needs sensors to perceive theoperating environment effectively.2.2.1.The sensors on end-effectorThe layout of sensors on end-effector, which includes a visionsensor, a position sensor, a collision sensor and a pressuresensor, is shown in Fig. 4. The vision sensor, which uses high-pixel colour charge coupled devices (CCD) video camera withuniversal serial bus (USB) interface and the video for windows(VFW) capture technology to form image acquisition system,plays a key role in completing image acquisition, fruit searchand recognition. To obtain a wide visible-field and not influ-encedby end-effector, the position of the vision sensoris in aneye-in-hand mode. In Fig. 4, it can be seen that there is thephotoelectricpositionsensorwithtwo pairsofinfrareddoublephotoelectric cells. In addition, the switch position sensorwhich was usually used to limit for electric cutting knife wasalso mounted on the position sensor. The arm began decel-eration when the end-effector moved towards the target fruitguided by the vision sensor and the first pair of photodiodeswas obscured by the fruit in the holder. The arm stopped andthe gripper clamped fruit when the two pairs of photocellswere obscured. At this point, both the pressure and collisionsensors adoptedforce sensitive resistance. When the pressuresensor on the gripper felt a certain pressure, the electric cutterrotated and cuts off pedicel. The cutter stopped working whenthe switch position sensor operated. The collision sensor wasused for obstacle avoidance during the process of harvesting.Analogue signals derived from the force sensitive resistanceand infrared photoelectric tubes are usually incompatiblewith the data acquisition module inside industrial computer.Therefore, they require modulation before transmission to thedata acquisition module. Fig. 5 shows the sensors signalmodulation circuit.2.2.2.The Sensor on manipulator for collision avoidanceControl of the angle of the rotating joints and position controlof the flexible joints was fulfilled using 8 Hall sensors,installed on the rotation joints of waist, the major arm, theminor arm and both ends of flexible joints. In the workingenvironment, the movement space of minor arm was wide;Fig. 3 e Photograph of the end-effector.PositionSensorPressureSensorVisionSensorCollisionSensorFig. 4 e Layout of sensors on end-effector.Fig. 5 e Sensors signal modulation circuit.Table 1 e Motion parameters of manipulator mechanicalstructure.Joint MotionparametersLift platform0 me0.8 mRotation joint of waist?180?e180?Rotation joint of major arm?80?e80?Rotation joint of minor arm?80?e80?Flexible joint0 me0.8 mbiosystems engineering 110 (2011) 112e122115and the probability of collision with obstacles was high.Therefore, the collision sensor was fixed in the minor arm todetect obstacles. Five groups of micro switches were fixed ondifferent positions in the minor arm to obtain real-timeinformation from obstacles. Noting that software program-ming processes signals conveniently, the five groups ofavoidance sensors were designated CR、CRU、CU、CLU、CLin accordance with their position. The distribution of theminor arm collision avoidance sensors is shown in Fig. 6.2.3.The vision systemsFor the vision system of the apple harvesting robot, the keyingredient was the image processing method that recognisedand located the fruit. It affects the robots dependability andalso determines its ability to directly, quickly and accuratelyrecognise in the fruit real time (Bulanon, Kataoka, & Okamoto,2004). However, in the earlier research (Bulanon, Kataoka, &Ota, 2002; Liu, Zhang, & Yang, 2008; Plebe & Grasso, 2001;Zhao, Yang, & Liu, 2004), there exist some unsolved issuessuch as low accuracy rate and time consumption, which tosome extent restricted the real-time and multitasking abilityof the apple harvesting robot in the natural environment.To overcome these shortcomings, a real-time automaticrecognition vision system consisting of a colour CCD cameraforcapturingoriginalappleimagesandanindustrialcomputer for processing images to recognise and locate thefruit was developed. Since the Fuji apples are the mostpopular in China, our research focused on this variety.The recognition and location procedure is as follows.Firstly, due to the natural environment and the imageacquisition device used, the original unprocessed apple imageinevitably includes noise that influences its quality. A vectormedianfilter wasappliedtoimageenhancementpre-processing. It can not only remove noise effectively andhighlights the apple fruit in foreground, but it also maintainsgood image edges.Secondly, most apple images acquired in the naturalconditionsusuallyincludebranchesandleaveswhichcomplicate matters. By using only a conventional imagesegmentation algorithm, it was difficult to achieve anticipatedeffect. Based on hue histogram statistics from the hue,intensity and saturation (HIS) model, the double thresholdand region growing method was employed to develop animage segmentation algorithm for identifying apple fruitfrom complex background. The chromaticity component isirrelevant when lightness is extracted and this avoided theinfluence of different illumination levels on the images. Thealgorithm was simple, and required little processing time.The apple features were extracted to determine the spatiallocation, and provide corresponding motion parameters forarm. For colour feature extraction, the chroma componentshue and saturation, are usually extracted as colour featuresfor recognition. However, in our study, apple fruit, branchesand leaves havespecific shapes, and their differences in shapeare large. Therefore, the shape feature is important in appleobject recognition. The selected rule of shape features wasbased on invariance in rotation, scale and translation (RST).Taking account of characteristics of apple fruit images,circular variance, variance ellipse, tightness, ratio betweenperimeter and square area were used to describe the outlineshape features of apple. These four feature vectors wereextracted as shape features. After the calculation of the cor-responding eigenvalues, they were used as feature vectors ofeach sample and used for training and classification.Finally, a new classification algorithm based on supportvector machine was constructed to recognise the apple fruit.Simulation and experiment shows that the support vectormachine (SVM) method with radial basis function (RBF) kernelfunction based on both colour features and shape featureswas found to be the best for apple recognition. Details of thealgorithm can be found in Wang, Zhao, Ji, Tu, and Zhang(2009).2.4.The control systemThe hardware structure is shown in Fig. 7. At the centre of thecontrol system was the host computer, which integrates thecontrol interface and all of software modules to control thewhole system. The sensor signal acquisition system andimage acquisition system constituted the input section whichwas used to collect external environment information for theFig. 6 e Layout of sensors on minor arm.Servodrivers14Incrementalphotoelectricencoder14Cutter of theend-ffectorUSB interfacePosition limitedsensorDrive motorfor cutterAirpumpCollision sensorInfrared sensorCCD Vision sensorElectricvalveSignalmodulationcircuitGripper of theend-ffectorAC Servomotors andload joints14Data acquisition moduleHost control computerRS232/RS422convertersFig. 7 e Hardware structure of apple harvesting robotcontrol system.biosystems engineering 110 (2011) 112e122116harvesting robot. The output section included a servo drivenmotor, air pump and end-effector.2.4.1.Host computerA Kintek KP-6420i (Kintek Electronics Co., Ltd., Miaoli Hsien,Taiwan, China) industrial computer with Intel Pentium41.7 GHz processor and 512 M memory was selected as the hostcontrol computer, which was responsible for collecting wholesensor signals, processing images online, calculating theinverse kinematics of manipulator and completing the controlalgorithm. The host computer transmitted instructions to thealternating current (AC) servo driver through a serial port tocontrol the joint motors of waist and arms. HighTek HK-5108(Shenzhen FangXingLiuTong Industrial Co., Ltd., Shenzhen,China) RS-232/RS-422 converters were chosen for serialcommunicationfunctions.Adataacquisitionmoduleinstalled inside host computer