手推式草坪修剪機(jī)設(shè)計(jì)【帶三維模型】
手推式草坪修剪機(jī)設(shè)計(jì)【帶三維模型】,帶三維模型,手推式,草坪,修剪,設(shè)計(jì),三維,模型
山東建筑大學(xué)
畢業(yè)設(shè)計(jì)開(kāi)題報(bào)告
學(xué)生姓名： 劉傳濤 學(xué) 號(hào)： 2003071256
班 級(jí)： 機(jī)本035
所在學(xué)院： 機(jī)電工程學(xué)院
專 業(yè)： 機(jī)械工程及自動(dòng)化
設(shè)計(jì)(論文)題目：手推式草坪修剪機(jī)設(shè)計(jì)
指導(dǎo)教師： 湯愛(ài)君 王全景
2007 年 4 月 23 日
山東建筑大學(xué)畢業(yè)論文開(kāi)題報(bào)告
班級(jí)：機(jī)本035 姓名：劉傳濤
論文題目
手推式草坪修剪機(jī)設(shè)計(jì)
一 選題背景和意義：
草坪是高度培育的特殊草地，隨著草坪面積的擴(kuò)大，品質(zhì)的提高，草坪業(yè)逐漸由單一的人工作業(yè)向半自動(dòng)化﹑機(jī)械化﹑自動(dòng)化過(guò)度，草坪作業(yè)的機(jī)械化已經(jīng)成為十分重要的課題。
大部分的草坪一直到19世紀(jì)中葉還在使用鐮刀來(lái)割草或放牧牛羊以保持草地的整齊性。隨著高爾夫球﹑網(wǎng)球以及足球等運(yùn)動(dòng)的興起，保持完整的草地做運(yùn)動(dòng)場(chǎng)便成為當(dāng)務(wù)之急。從20世紀(jì)起出現(xiàn)以機(jī)器代替手工的趨勢(shì)，于是好的修剪機(jī)遂成為草坪管理的必需品。
草坪修剪機(jī)分滾切式﹑旋刀式﹑剪切式三類，按動(dòng)力又可分為手動(dòng)與機(jī)動(dòng)兩類。機(jī)動(dòng)有乘坐式與手推式，北京園林機(jī)修廠JUS—420型旋刀式修剪機(jī)系單缸四沖程汽油機(jī)驅(qū)動(dòng)，功率2.6Kw,一把旋刀，幅寬420mm，每班可修剪2000m2,整機(jī)質(zhì)量40Kg。上海園林機(jī)械廠JCG540Ⅱ型滾切式草坪修剪機(jī)，乘坐手推兩用式，有兩個(gè)前進(jìn)檔，IE50F—2汽油機(jī)功率2.3kw，5片滾刀，幅寬540mm，該機(jī) 高，但用于坡地時(shí)機(jī)組穩(wěn)定性較差。小庭院的草坪可用上海生產(chǎn)的JCG—250Ⅱ型手推草坪修剪機(jī)，人推動(dòng)前進(jìn)并使6個(gè)滾刀旋轉(zhuǎn)切割草坪，幅寬250mm。德國(guó)SOLO522型草坪修剪機(jī)為手推式，動(dòng)力系單缸四沖程汽油機(jī)，功率為2.3kW，刀片為剪切式，幅寬800mm。該產(chǎn)品的特點(diǎn)是刀片耐磨，機(jī)具噪聲低，振動(dòng)小，對(duì)坡地適應(yīng)性好。改換工作部件可作掃雪工具。
旋刀式剪草機(jī)適用于草高25~80mm低要求的草坪，剪幅在0.5~20.m之間。滾切式剪草機(jī)適用于草高3~80mm的高要求草坪，剪幅0.5~5.0m之間。
修剪是維持優(yōu)質(zhì)草坪的重要作業(yè)，它主要是定期除掉草坪草枝條的土表部分。在特定的草坪上，根據(jù)所需要的培育強(qiáng)度，修剪的目的是在特定的范圍內(nèi)保持頂端生長(zhǎng)，控制不理想的、不耐剪的營(yíng)養(yǎng)生長(zhǎng)，維持一個(gè)觀賞和游息草坪，產(chǎn)生一個(gè)真實(shí)的擊球表面或發(fā)展草坪作物。
修剪的質(zhì)量由所使用的剪草機(jī)的類型和割時(shí)草地的狀況決定。因此，隨各種特殊功能的開(kāi)發(fā)，應(yīng)重視修剪機(jī)具的發(fā)展。
我國(guó)幅原廣闊，地區(qū)差異很大。草坪的功能不同，對(duì)機(jī)具的要求也不同，加之各地區(qū)經(jīng)濟(jì)發(fā)展不平衡，用戶的購(gòu)買能力也有差異，因此草坪機(jī)械只有開(kāi)發(fā)系列產(chǎn)品才能滿足不同市場(chǎng)的需要。
另外，有些草坪機(jī)具一年只用幾次，因此草坪機(jī)具在以草坪作業(yè)為主項(xiàng)的同時(shí)，應(yīng)配備一些附加裝置，擴(kuò)大其使用功能，提高機(jī)具的利用率。
二 難點(diǎn)和關(guān)鍵問(wèn)題：
（1） 圍繞著零件圖紙進(jìn)行分析，做出綜合性的分析。
（2） 對(duì)零件進(jìn)行綜合布局，畫(huà)出總設(shè)計(jì)的圖紙。
（3） 在設(shè)計(jì)中應(yīng)合理的選擇材料，減少應(yīng)力集中（如尖角、銳邊、表面；粗糙度等）.控制尺寸公差。
（4）本課題的難點(diǎn)是，根據(jù)電機(jī)的功率和人行走的速度換算出三級(jí)變速齒輪的傳動(dòng)比，電機(jī)和人力兩種動(dòng)力間的轉(zhuǎn)換。
三 文獻(xiàn)總述
從地球有了人類開(kāi)始，我們就磨削石塊，制造工具，開(kāi)始了工具革命的過(guò)程，一直延續(xù)至今,最早的剪草工具是小鐮刀和手剪。但是I803年美國(guó)專利機(jī)構(gòu)公布了剪草機(jī)的第一個(gè)專利。然而未形成商品。在大西洋披岸 ，一位名叫Edwin Budding的英國(guó)人發(fā)明了滾刀式剪草機(jī)他是一個(gè)紡織工人，監(jiān)視旋轉(zhuǎn)式機(jī)械用于修剪呢絨絨毛。他決定將這一工作原理應(yīng)用于割草 。
1855年 Budding的剪草機(jī)在英國(guó)問(wèn)世并受到歡迎,Henxy將它引入美國(guó)。
1877年在 Richmond，McGuin試圖發(fā)展這種剪草機(jī)使其容易推動(dòng)更加實(shí)用 1855年美國(guó)公司一年生產(chǎn)近50000臺(tái)草坪剪草機(jī).其構(gòu)造與今天的手推式剪草機(jī)類似 。
1890年還是在英國(guó)開(kāi)始設(shè)計(jì)有動(dòng)力驅(qū)動(dòng)的剪草機(jī)。第一個(gè)成功的動(dòng)力剪草機(jī)由LeyLandMotors制造，為蒸汽動(dòng)力型，然而，另一個(gè)技術(shù)革命使它不久即被淘汰。
1885年德國(guó)工程師 Gottlieb Daimler 發(fā)展了一種小型內(nèi)燃機(jī)，并首先應(yīng)用在自行車上。建立第一個(gè)摩托車。適用的動(dòng)力源導(dǎo)致發(fā)展汽車，飛機(jī)甚至洗衣機(jī)，隨之應(yīng)用于動(dòng)力剪草機(jī)和園藝機(jī)具，另一個(gè)英國(guó)公司1902年皇家農(nóng)業(yè)協(xié)會(huì)舉辦的展覽會(huì)上展出了6馬力的動(dòng)力剪草機(jī).
美國(guó)工程師和革新家在本世紀(jì)初的十年中,也致力于動(dòng)力剪草機(jī)的研究1909年Leoni取 到了動(dòng)力型機(jī)械式剪草機(jī)專利Leoni的動(dòng)力型剪草機(jī)由汽油機(jī)驅(qū)動(dòng)。整個(gè)裝置行走由馬拉。大約在第1次世界大戰(zhàn)前不久 ，動(dòng)力型剪草機(jī)開(kāi)始用于家庭。George 是一位實(shí)業(yè)家和開(kāi)發(fā)者。他最早開(kāi)始經(jīng)營(yíng)商業(yè)，他的馬達(dá)剪草機(jī)公司曾定名為“立即成功 ”。他設(shè)計(jì)的發(fā)動(dòng)機(jī)安裝在滾刀式剪草機(jī)上。一直保持到1950年。
接著又有其他廠家生產(chǎn)類似的機(jī)械。到1927年Hardware Age“年度消費(fèi)者目錄”登出了近21家公司生產(chǎn)動(dòng)力型草坪剪草機(jī)其中的兩家廠商一波倫 (Bolens)和蔣索波森(Jacobsen)存在至今,并成為著名廠商 。
美國(guó)克里夫蘭市的聯(lián)合鑄造供應(yīng)公司制造的草坪剪草機(jī)備有集草袋和自動(dòng)離臺(tái)器當(dāng)?shù)镀龅酵饨缱枇r(shí)即與傳動(dòng)裝置自動(dòng)分離。
美國(guó)費(fèi)拉德?tīng)柗苼啠ㄙM(fèi)城）的草坪剪草機(jī)公司在廣告上登出了全系列的手動(dòng)馬拉和動(dòng)力驅(qū)動(dòng)的剪草機(jī)，從1922年開(kāi)始推出30和40英時(shí)的可乘式剪草機(jī)。
事實(shí)上，旋刀式剪草機(jī)是在戰(zhàn)前發(fā)展的，然而直到1次世界大戰(zhàn)之后才推廣。1933年 ,Bolen提出的旋刀式剪草機(jī)專利與今天使用的類似 ，有跡象表明，在 1920年之前此種旋刀式剪草機(jī)只是為私人使用。1938年出現(xiàn)的旋刀式剪草機(jī)獲得了商業(yè)上的成功Howard為 了解決大面積雜草的修剪問(wèn)題 一 他立即在他的地下車間開(kāi)始了研制工作。
Gravely是個(gè)花匠，為了解決他花園的耕作問(wèn)題，使用手推犁刀，1920年他開(kāi)始生產(chǎn)園藝用拖拉機(jī)，并 取得動(dòng)力犁的專利，更早的園藝拖拉機(jī)是在1919年 GiLson Brothers制造 ，Beeman拖拉機(jī)公司銷售。1927年Hardware Age列出11個(gè)園藝拖拉機(jī)制造商。包括克里夫蘭市的Barcer～ Raulang公司，該公司推出了電動(dòng)型園藝拖拉機(jī)。
1910年瑞士Konrad應(yīng)用除根的耕作機(jī)具。該裝置不是第一個(gè)轉(zhuǎn)子式中耕機(jī) (早在1857年就有此種機(jī)型)，但是早期的機(jī)型重量大，達(dá)數(shù)噸，其動(dòng)力為蒸氣機(jī)式，與現(xiàn)代機(jī)型完全不同。
1911年德國(guó)的Siemens—Sehckert～ Werk公 司 ，在它的專利基礎(chǔ)上制造了最早的電動(dòng)機(jī)驅(qū)動(dòng)的中耕機(jī)。但是沒(méi)有得到發(fā)展。不久被汽油機(jī)所取代 。
1930年Siemens決定將機(jī)器引入美國(guó)，他來(lái)到美國(guó)同費(fèi)城的Kol sey合作。Kelsey 建立 了Rototiller公司，銷售從歐州引進(jìn)的機(jī)器。1934年Kelsey的Rototiller公司生產(chǎn)了它的第一臺(tái)美國(guó)制造的中耕機(jī) 。
Rototiller公司早期競(jìng)爭(zhēng)對(duì)手之一是 Arien公司，Arien和他的兒子成立了一個(gè)公司，聲稱為美國(guó)第一家生產(chǎn)轉(zhuǎn)子式中耕機(jī)的公司。Arien公司的第一臺(tái)轉(zhuǎn)子式中耕機(jī)重900磅，未獲得成功。隨著 1次世界大戰(zhàn)爆發(fā)，園藝機(jī)械的生產(chǎn)也隨之停頓。
應(yīng)該指出，無(wú)論是 Ariens公司或 Rototiller公司的中耕機(jī)都是后齒型一1936年 Roto--Hoe公司生產(chǎn)了前齒型中耕機(jī) ，在戰(zhàn)爭(zhēng)初期，它們銷售很慢，而前齒型中韉機(jī)在戰(zhàn)爭(zhēng)之后作為家用設(shè)備獲得成功 。
鏈鋸的發(fā)展也要追溯到 Ⅱ次世界大戰(zhàn)爆發(fā)之前 。第一具鏈鋸是在1904年。直到戰(zhàn)爭(zhēng)之后才形成商業(yè)產(chǎn)品。Sfihl的鏈鋸重105 磅 ．是在1927年。由兩人操作。
動(dòng)力草坪清掃機(jī)也出現(xiàn)在戰(zhàn)爭(zhēng)之前。創(chuàng)建者是 Parker Pattern。他的兒子 Edwin Parker于1919年進(jìn)一步發(fā)展 。1931年 Edwin作為公司董事長(zhǎng)推出公司第一臺(tái)動(dòng)力草坪清掃機(jī) 。
在園林機(jī)械發(fā)展的歷 史上 。2次世界大戰(zhàn)是一個(gè)轉(zhuǎn)折點(diǎn)，2次世界大戰(zhàn)之后 ，整個(gè)國(guó)家得到復(fù)興，園林機(jī)械也得到重大發(fā)展。允許復(fù)役軍人低價(jià)買房不付現(xiàn)金，大批建設(shè)房屋并 出售。促使園林設(shè)備得到空前發(fā)展。
戰(zhàn)后，鏈鋸也得到改進(jìn)。1944年Claude—Poulan監(jiān)視德國(guó)人—戰(zhàn)爭(zhēng)囚犯在東德克薩斯州砍樹(shù)。兩人操縱鏈鋸。尚需第三個(gè)人控制撬扛。戰(zhàn)后，他立即著手建立裝有發(fā)動(dòng)機(jī)的鏈鋸 。生產(chǎn)鏈鋸的公司也在不斷增長(zhǎng)。橫過(guò)大西洋，Solo(在1948年 )和 Stihl(在1950 年)是首批生產(chǎn)一人操縱鏈鋸的公司 Stihl承認(rèn)。最初的一人操縱的鏈鋸重量較重。直到1954年才生產(chǎn)了輕重量級(jí)的鏈鋸（重31 磅）。與此同時(shí)，其他廠商也發(fā)展了輕重量級(jí)的鏈鋸。例如1961年Iombard Governor 公司出售一種16英寸，27磅鏈鋸 Steve和Dave HOH試圖清除他家占地面積為240畝的莊園雜草。這促使他建立了一個(gè)大鐮刀。1949年曾形成商品。銷售灌木切割機(jī) 。
在同一時(shí)期，人們利用內(nèi)燃機(jī)為動(dòng)力驅(qū)動(dòng)掃雪裝置，1948年Henry Ariens發(fā)展了一種拋雪機(jī)的工作樣機(jī)。直到1960年初才進(jìn)入市場(chǎng)。
1959年隨著園林機(jī)械工業(yè)的發(fā)展。人們意識(shí)到需要興辦一個(gè)雜志。Bill Qu Jnn．自行車 雜志的發(fā)行人開(kāi)始創(chuàng)辦草坪設(shè)備期刊 ，1969年，該雜志更名為戶外動(dòng)力設(shè)備 （OPE）。
在雜志創(chuàng)辦時(shí)，按照產(chǎn)品銷售的型號(hào)與今天幾乎差不多。但是隨著工業(yè)的發(fā)展，操作者 的要求在改變，必須考慮操作安全，環(huán)境污染及其他關(guān)心的問(wèn)題。
1971年George Ballas為了控制自已莊園樹(shù)根周圍的雜草，他制造了多頭帶式修剪機(jī) (繩索式割灌機(jī))。達(dá)到了理想的效果。1977年 Weed Eater公司推出了單繩帶式修剪機(jī) 。
當(dāng)然．園林機(jī)械設(shè)備的歷史沒(méi)有結(jié)束．如同沒(méi)有明顯的起點(diǎn)一樣，沒(méi)有終點(diǎn)它將繼續(xù)擴(kuò)大領(lǐng)域?yàn)槿祟愖鞒鲂碌呢暙I(xiàn)。
四 方案論證
根據(jù)電機(jī)的功率和人行走的速度換算出三級(jí)變速齒輪的傳動(dòng)比，電機(jī)和人力兩種動(dòng)力間的轉(zhuǎn)換。
傳動(dòng)裝置是大多數(shù)機(jī)器或機(jī)組的主要組成部分。實(shí)驗(yàn)證明，傳動(dòng)裝置在整臺(tái)機(jī)器的質(zhì)量和成本中占有很大比例。機(jī)器的運(yùn)轉(zhuǎn)性能和運(yùn)轉(zhuǎn)費(fèi)用在很大程度上決定了傳動(dòng)系統(tǒng)的優(yōu)劣。因此，不斷提高傳動(dòng)裝置的設(shè)計(jì)和制造水平具有極其重要的作用。
（1）剪切裝置
剪切裝置由滾刀和底刀組成，滾刀和底刀結(jié)構(gòu)如下圖所示。底刀用六角螺栓固定在底刀架上，剪草時(shí)位置不動(dòng)，刀刃為直線型。滾刀的刀片形狀為螺旋曲面，刀刃為螺旋線，五片刀片均勻分布固定在刀架上。剪草時(shí)，滾刀向前轉(zhuǎn)動(dòng)，刀刃由一端開(kāi)始與底刀刃逐點(diǎn)組成剪口，草隨著滾刀刀片螺旋面的旋轉(zhuǎn)被卷進(jìn)剪口內(nèi)，并被剪斷。上下刀刃剪草過(guò)程始終為點(diǎn)接觸。
圖4.1滾刀和底刀外形圖
（2）離合器裝置
離合器裝置是為了使剪草機(jī)正向剪草反向停止旋轉(zhuǎn)而特意設(shè)置的工作裝置，它是由齒輪和其內(nèi)的彈簧和鋼球組成。剪草時(shí)，鋼球在彈簧的作用下壓緊齒輪內(nèi)壁迫使起和其他齒輪嚙合，從而帶動(dòng)滾刀旋轉(zhuǎn)然后與底刀相切剪草的，當(dāng)手扶手拉動(dòng)剪草機(jī)向后運(yùn)動(dòng)時(shí)，由于該齒輪的轉(zhuǎn)速大于與之聯(lián)結(jié)的軸的轉(zhuǎn)速，這樣在超越離合器作用下該齒輪將相對(duì)軸做超越運(yùn)動(dòng)，使得滾刀軸靜止不動(dòng)，不與齒輪軸發(fā)生干涉。
五、進(jìn)度安排
第1、2周 調(diào)查查閱 收集查閱資料
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第13、14周 詳細(xì)設(shè)計(jì)
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第17周 撰寫(xiě)畢業(yè)設(shè)計(jì)說(shuō)明書(shū)
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Ming Cong and Bo Fang School of Mechanical Engineering, Dalian University of Technology Dalian, 116024, China * This work is supported by national natural science fund #50675027to Ming Cong Abstract - This paper presents a multisensor system for combining measurements from ultrasonic sensors and navigation for robot mowers. The proposed sensing system enables robot mowers to mapping unknown environments. It is important for an autonomous robot mower to explore its surroundings in performing the task of localization and navigation for mowing. Because of the complexity of the environment, one simple kind of sensors is not sufficient for robot mower to accomplish these tasks. We develop a robot mower equipped with DSP TMS320F2812 as its CPU. The sensing system integrates with ultrasonic sensors, infrared sensors, collision sensors, encoders, a temperature sensor and an electronic compass. A method of high accuracy ultrasonic ranging technology based on wavelet transform is reported to improve the measurement precision of ultrasonic sensors. Simulation studies show that the proposed multisensor fusion method is very effective for the navigation of robot mowers. Experimental results indicate that this sensing system based on generalized auto-correlation method for obstacle detection and localization shows great potential for providing a high performance-to-price ratio and robust solution for robot mowers in dynamic working condition. Index Terms - multisensor fusion, ultrasonic sensors, robot mower, mapping, navigation I. INTRODUCTION Lawn mowing is considered by many to be one of the most boring and tiring routine tasks. The environmental robots are needed urgently to perform the task. Some predictions indicate that the robot mowers will be one of the most promising personal robot applications and have substantial market in the world. Therefore, the concept of Intelligent Robot Mower (IRM) had been proposed for the first time in 1997 s annual conference of the OPEI (Outdoor Power Equipment Institute) 1. The robots mainly face to the general families to help the busy people and the hypodynamic old folks save the payments for hiring labours, also remove people from noise, pollen and danger of mowing blade. The robot mowers serve for home care as the outdoor mobile robots, actually kind of intelligent mechatronics devices for environment clean-up 23. The important thing is that the robot mowers are representative of some area-covering environmental robots used not only for indoor floor cleaning as in 4 but also in hazardous environments such as removing landmines, cleaning up radiant points and prospecting for resources etc. The robot mowers get great challenges differing from indoor mobile robots. The robot mowers use sensors to understand environments as well as their real-time states for obstacle avoidance, map building, location and navigation in the whole work area. Because of the complexity of the environment, one simple kind of sensors is not sufficient for robot mower to accomplish these tasks. It is necessary to combine the observed sensor data coming from different sensors to reduce the uncertainties of the robot in any working environment. To merge the information from the various sensors, robust and real-time sensor fusion is required 5. In cases of sensor error or failure, multisensor fusion can also reduce uncertainty in the information and increase its reliability. A sensing system of low cost, low power consumption, high performance is described. The detecting range of ultrasonic sensors is 0.3m5m, they provide good range information. However, uncertainties in ultrasonic sensors caused by the specular reflection from environments make them less attractive. The detecting range of infrared sensors is 0.02m1m, they can detect the obstacles within the ultrasonic sensor s blind zone. In order to satisfy the needs of robot mowers for the low cost and high accuracy ranging technology, the research on the high accuracy ultrasonic ranging technology based on wavelet transform (WT) is reported to improve the measurement precision of ultrasonic sensors. Measurement data gathered from the sensing system are integrated to avoid the robot mower from unknown obstacles and plan an optimum, reliable and realizable plan completely coverage of entire working area. Finally, simulation studies and experimental results show the effectiveness of the sensing system for the navigation, obstacle detection and localization of robot mowers. II. SYSTEM HARDWARE OF IRM The IRM uses DSP TMS320F2812 as its CPU, including four units: vehicle system, cutting system, sensing system and control system. The sensing system is used to collect the external dynamic information of the working environment for obstacle avoidance, map building, navigation and localization. It is also used to detect vehicle system s movement parameters and cutting mechanism s working status. The controller compares the acquired information with the database, and then sends out revisory and accurate command to the robot to perform its tasks. The hardware of the IRM is shown in Fig. 1. Multisensor Fusion and Navigation for Robot Mower* 978-1-4244-1758-2/08/$25.00 2008 IEEE.417Proceedings of the 2007 IEEEInternational Conference on Robotics and BiomimeticsDecember 15 -18, 2007, Sanya, China Fig. 1 Hardware overview of IMR The robot must be physically strong, computationally fast, behaviourally accurate and safety. It should have the ability to perform on its own, and required no human intervention during the whole or most part of the mowing period. The IRM is modularized designed and each unit of the IRM is relatively independent. Modularized design makes the maintenance much easier. Any broken unit of the IRM can be replaced directly without influencing the functions of other units. III. SENSING SYSTEM A. Ultrasonic Sensor Unit Because ultrasonic sensors can provide good range information based on the time of the flight (TOF) principle, mainly due to their simplicity and relatively low cost, they have been widely used in mobile robots for obstacle avoidance, map building and so on. This type of external sensor is very good in obstacles distance measurement. The main lobe of the sensitivity function is contained within an angle of 20 degrees, as shown in Fig. 2 6. A number of tests showed that the range accuracy of the sensors is in the order of 2cm. Fig. 2 Typical intensity distribution of an ultrasonic sensor On IRM, we set up a sensor array which consists of 12 ultrasonic sensors spaced 30 degrees apart. The ultrasonic signals can cover all the space around and satisfy the space requirement about which robot can detect the environmental signals. Classical techniques used in ultrasonic transducers are based on TOF measurement, which calculates the distance of the nearest reflector using the speed of sound in air and the emitted pulse and echo arrival times. The distance d to a reflected object is calculated by () 2dct= (1) where c is the speed of sound, and t is the time-of-flight. The TOF method produces a range value when the echo amplitude first exceeds the threshold level after transmitting, ignoring a second echo from a further reflector. The ultrasonic sensor unit includes a trigger pulse generation unit, a multi-channel selection unit and an echo receiving unit. A sensor interface circuitry designed to send and receive ultrasonic sound pulses catches always the first returning echo. The range data related to an object is considered to be on the conic axes even if it is located off the axes. The ultrasonic wave typically has a frequency between 40 and 180 kHz, and the frequency of the ultrasonic sensors used in the system is 40 kHz. The beam angle is 20 degrees. The 40 kHz PWM pulse is generated by the general-purpose timer unit of DSP. To drive the transmitter effectively and not to bring much vibration, an 8 cycle burst of ultrasound at 40 kHz is sent out once a time. When the ultrasonic pulse is emitted, the sensor will experience “ringing” . Ringing caused by the transmitted pulse can cause the receiver to detect a false echo. This problem is solved by not enabling the capture interrupt of DSP until a delay interval has passed. This means that the ranger can not detect an object whose distance from the sensor is less than half the distance that sound travels during the delay interval. This is the blind zone of the ultrasonic sensor, as shown in Fig. 3. Trigger pulseEmitted signalReceived signalTOFBlind zoneEcho Fig. 3 The sketch map of ultrasonic transmission and reception B. Infrared Sensor Unit and Other Sensors To overcome the ultrasonic sensor s blind zone, infrared sensors are added. The infrared sensors can detect obstacles within 20cm, which patch up the problem caused by the blind zone problem of ultrasonic sensors. This unit has 16 infrared sensors. Each infrared range finder has a conic view of 6 degrees which is the main lobe of the sensitivity function. This sensor has a useful measuring range of a target up to about one meter with high accuracy. A number of tests showed that the range accuracy of the sensors is in the order of lcm. In order to save the DSP s resource, 16 infrared sensors are connected with DSP TMS320F2812 s data interface 418instead of the IO interface. This kind of architecture can also read the sensors status at the same time, ensuring the real-time capability of the system. A sensor interface circuitry designed to send and receive infrared pulses catches always the first retuning echo to process its amplitude. Robot mower works in an outdoor environment, where the temperature changes rapidly. The changing of temperature will affect the speed of sound. Therefore, a temperature sensor is used to guarantee the precision of the ultrasonic sensor. Collision sensor is a group of sensitive swatches, which used to prevent the damage caused by unexpected collision. Because moist environment do harm to the circuit of the IRM, humidity sensors are introduced to detect the humidity of the environment. Although these sensors are not absolutely necessary for an autonomous robot mower, they can provide helpful functions to make the work availability and safety. IV. SENSOR-BASED NAVIGATION A. Mapping As seen in Fig. 4, a reference direction x is defined and the robot coordinates are shown asRx,Ry. By the help of an electronic compass built in on the robot 7, the anglei, which is the ith sensor s angle from the 1st sensor, can be easily measured. Actually if only the angle S (heading angle of the robot) is measured, other sensor angles can be found as iSi=+ (2) where iis the angle to the our world coordinate center. The number of maximum sensor group on the ultrasonic ring is n, and the radius is r (in our system n=12 and r=0.25m). The distance between the origin and the center of the ring is R, and reference angle to the center is. The reference position of the robots center is (Rx,Ry). The distance from the origin to object which is detected by the ith sensor data on the two dimensional plane is callediR. Now letidmdenote measured value which is combined data from the ultrasonic and infrared sensors, for the exact distanceiR. There will be an error i between these values as iiidmd=+. (3) In this work we naturally assume that i is a uniform random variable in the range of (-W, W). Here W denotes the maximum distance measurement error. Here the problem is, givenRx,Ry, r, 12,n ?, and 12,ndm dmdm?, to estimate the coordinates of the occupied cells ixand iy(or equivalently iR) in most efficient way. The equations involving the detected object can be written as 222()cos()()sin()iRiiRiiRxrdyrd=+ (4) 222()2()( cos()sin()iiiiiRRrdrdxy=+ 222()2()cos()iiiRiRRrdrd=+ (5) yxxy RR ?ddO Fig. 4 The robot position on x-y section The equations involving the robot due to the object can be written as 222()cos()()sin()iiiiiiRxrdyrd=+ (6) 2222()2()(cos()sin()iiiiiiiiRxyrdrdxy=+If we define the positions as: 11,TTiniiPp ppx y=?, then we have 222()2() cos(),sin()iiiiiiiRRrdrdyP=+ (7) After the inserting the 2iRin 2R, ()cos()cos(),sin()iiiiiirdRyP+= (8) Here again we have n such equations. And we write them in matrix form imA P= (9) And if we introduce new matrix as ()cos(),sin()iiiiLP= and 0,0=, then (10), can be written as 11112cos()()()cos()()RnRnnnrdmRLpLrdmRLp+ ?=?+ ?Here if we perform the least squares estimate foriP, we obtain 1()()TTlsqiPA AA m= (11) Thus we find the best squares estimate of the positions. B. Simulation Studies Sensor-based navigation has been tested with simulation to shown the usefulness of this sensor fusion method in the two environments respectively as shown in Fig. 5 and Fig. 6. The mower has been primarily tested in a structured laboratory as shown in Fig. 5. Start at (0.3m, 0.5m, 0degree), a virtual 419robot was driven around a virtual square corridor one time. The walls in the artificial environment are denoted by the real map. The entire vehicle is self-contained. It has a maximum travel speed on 0.4 m/s. The laboratory area was surveyed out to a 10cm grid with accuracy better than about 1cm. To extract the mapping, a start and goal points were presented. The robot position and orientation were established by the electronic compass 8. Fig. 5 Data collection and navigation result in structured environment The result in Fig. 5 demonstrates the mapping quality and the usefulness of this sensor fusion method. In the tests, we find that the average error () in estimating the position of the obstacles in the environment was in the range of -0.2, 0.2m. In the simulations we see that ()lsq iPin (11), obtained does not satisfy ()ilsq iRP=which actually should. In the case a better estimate for the positions can be given as ()()()ieilsqilsqiRPPP= (12) In this case, estimate for the angle i does not change but the estimate for distanceiR is scaled to it best estimate. Therefore for the position, the distance estimate iR remains the same as before, while the least squares estimate works only for the anglei . Simulations show that this way produces more accurate results. Fig. 6 The simulation result of wall-following behavior Wall following was selected for the initial problem domain because it is a fairly simple problem to set up and evaluate 9. It also lays the groundwork for more complex problem domains, such as maze traversal, mapping and complete coverage path planning which is used on lawn mowing and vacuuming. The simulation result of wall-following behavior shown in Fig. 6, and the experimental result in Fig. 6 demonstrate that the IRM have the capability to perform its mowing task in unstructured environment. The program of sensor-based navigation simulation in Fig. 5 is given below. Sub Main Dim PI,Fcr,Fct,X_target,Y_target,X,Y As Single Dim X_grid, Y_grid, i, j, C As Integer Dim Frx,Fry,d, dist_targ, rot, Fx, Fy As Single Dim Fcx,Fcy, Rx,Ry As Single PI=3.1415927 Fcr=1 Fct=1 X_target=GetMarkX(0) Y_target=GetMarkY(0) SetCellSize(0,0.1) Set cell size 10 cm x 10 cm SetTimeStep(0.1) Set simulation time step of 0.1 seconds Do Start main loop X=GetMobotX(0) Present mobot coordinates (in meters) Y=GetMobotY(0) X_grid=CoordToGrid(0,X) indexes of cells where the Y_grid=CoordToGrid(0,Y) mobot center is MeasureRange(0,-1,3) Perform a range scan and update the Certainty Grid (max. cell value=3) Frx=0 Fry=0 Each ocuppied cell inside the windows of 33 x 33 cells applies a repulsive force to the mobot. For i=X_grid-16 To X_grid+16 For j=Y_grid-16 To Y_grid+16 C=GetCell(0,i,j) If C0 Then d=Sqr(X_grid-i)2+(Y_grid-j)2) If d0 Then Frx=Frx+Fcr*C/d2*(X_grid-i)/d Fry=Fry+Fcr*C/d2*(Y_grid-j)/d End If End If Next Next dist_targ=Sqr(X-X_target)2+(Y-Y_target)2) Fcx=Fct*(X_target-X)/dist_targ Fcy=Fct*(Y_target-Y)/dist_targ Rx=Frx+Fcx Ry=Fry+Fcy rot=RotationalDiff(0,X+Rx,Y+Ry) shortest rotational difference between current direction of travel and direction of vector R SetSteering(0,0.5,3*rot)mobot turns into the direction of R at constant speed and steering rate proportional to the rotational difference StepForward Loop Until dist_targ0.1 Loop until mobot reaches the target End Sub 420V. ULTRASONIC RANGING TECHNOLOGY BASED ON WT Unfortunately, the practical received multi-echoes has time-varying property and is a typical non-stationary signal because the influence of the environmental complexity and the noise. Furthermore, the noise mixed in the ultrasonic pulse-echo is Non-Gaussian white noise but colored noise, and correlated with the target echo. The TOF method can not be used directly in such conditions. Referencing the generalized correlation method for estimation of time delay 10, we put forward the generalized auto-correlation method for estimation of time-of-flight based on wavelet transform 11 and present in Fig. 7. Fig. 7 Delay estimation of generalized auto-correlation based on WT Where( ) tis the mother wavelet and( )atis the daughter wavelet. The coefficient is the scale (or scaling factor) andis the time displacement. The wavelet transform of the signal( )x tis( )y t. Actually this is a filtering process of the ultrasonic echo using a multitude of bandpass filters of equalQ, which is equivalent to the whitening filter of the generalized correlation method for estimation of time delay, in order to eliminate the input noise which can influence the following processing.( )yyRcan be found as ( ) ( ) ()( ) ( )()yyxxaaRE y t y tRttt= As there has the relationship of Fourier transform between auto-correlation function( )yyR and his power spectrume:2( )( )( )()()( )()yyyyxxxxGF RGaaGa= We obtain the generalized auto-correlation function as Last, the peak values of( )yyRare detected to accomplish the estimation of TOF and calculate the real ultrasonic velocity. Fig. 8 Noisy ultrasonic echo Fig. 9 Denoised echo using WT Fig. 10 Auto-correlation function( )yyR Fig. 11 Peak detection The noisy ultrasonic echo is shown in Fig. 8, and the denoised ultrasonic echo by wavelet transform is shown in Fig. 9. It is obvious that the noise mixed in the ultrasonic echo is effectively eliminated after WT operation. The auto-correlation operation ( )yyRof the denoised ultrasonic echo is shown in Fig. 10. Fig. 11 shows the envelope of( )yyRthrough Hilbert transform. As we can see, if the abscissa of every peak point is determined, the estimation of TOF?ND can be calculated. Considered the attenuation of the ultrasonic echo and the demand of the high precision in practice, only the former four echoes are used to estimate the TOF. The values of the TOF estimation are ?3 , 2 ,2 ,3DDD DDD, which are symmetrical to the x-axis. Using this method, the estimation of the ultrasonic velocity can be calculated. So far, an obstacle detection and localization system has been implemented successfully. By means of above method, an obstacle detection and localization system has been implemented successfully. The generalized auto-correlation method based on wavelet transform is put forward to realize the real-time ultrasonic velocity measurement, and this method can ()11( )( )( )( )22gjjyyyygyyRGedGed=?421eliminate the influence of temperature, humidity and wind on ultrasonic velocity measurements when the robots are working in dynamic condition. And this sensing system based on generalized auto-correlation method shows great potential for providing a robust solution for robot mowers in dynamic working condition. VI. EXPERIMENTAL RESULTS We measure the distance between the robot and plane objects using the ultrasonic sensors. The measured results and the actual distances are shown in TABLE I. TABLE I THE EXPERIMENTAL DATA OF THE ULTRASONIC SENSORS (unit: cm) Actual distance Measured value1 Measured value2 Average error 30 30.62 30.61 2.50% 40 40.70 41.69 1.73% 50 50.64 50.67 1.31% 60 60.73 60.73 1.22% 70 70.81 70.84 1.19% 80 81.09 81.04 1.33% 90 91.10 91.13 1.24% 100 98.82 99.15 1.02% 150 148.24 148.37 1.13% 200 201.85 201.85 0.93% 250 252.71 252.74 1.09% 300 302.52 302.58 0.85% 350 347.
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