發(fā)布時間：2018-10-23 21:12

【摘要】：在特征尺寸為微米和亞微米量級的物體上進(jìn)行加持、吸附、抓取、轉(zhuǎn)移、裝配和注射等操作稱為微操作。執(zhí)行微操作的器械設(shè)備稱為微操作系統(tǒng)或者微操作機(jī)器人。近年來,微操作系統(tǒng)被廣泛地應(yīng)用到微機(jī)電系統(tǒng)MEMS(Micro Electro Mechanical System)、微光電子機(jī)械系統(tǒng)MOEMS(Micro Opto Electro Mechanical System)和生物微機(jī)電系統(tǒng)Bio MEMS(Biological Micro Electro Mechanical System)等。將微操作機(jī)器人系統(tǒng)和顯微視覺信息相結(jié)合形成的顯微視覺伺服控制系統(tǒng)并使其具有與外部環(huán)境進(jìn)行智能交互能力,是當(dāng)今微操作機(jī)器人系統(tǒng)研究和發(fā)展的一個主要方向。目前對微操作系統(tǒng)的研究范圍已經(jīng)從理論研究發(fā)展到了應(yīng)用設(shè)計。因此,微操作系統(tǒng)領(lǐng)域的未來發(fā)展熱點(diǎn)之一是將其大規(guī)模的應(yīng)用到工業(yè)生產(chǎn)上。為了實(shí)現(xiàn)這一目標(biāo),微操作系統(tǒng)自動化和智能化的水平和質(zhì)量在發(fā)展過程中將起到關(guān)鍵的作用。本文圍繞微操作系統(tǒng)的自動化問題進(jìn)行了系統(tǒng)的整體規(guī)劃,自行構(gòu)建了一套完整的顯微立體視覺伺服微定位控制系統(tǒng)。系統(tǒng)包括:末端執(zhí)行器模塊,運(yùn)動控制模塊和顯微視覺模塊,并在此基礎(chǔ)上對微操作系統(tǒng)中顯微立體視覺伺服的成像模型和系統(tǒng)的微定位控制進(jìn)行了重點(diǎn)研究。針對顯微視覺伺服系統(tǒng)中深度信息獲取問題,本文基于顯微視覺模塊建立了G(Greenough)型和CMO(Common Main Objective)型兩種結(jié)構(gòu)下的體視顯微鏡SLM(Stereo Light Microscopy)的成像模型。采用這兩種視覺模型可以直接從3D場景中獲取物體的視覺信息,避免了微操作系統(tǒng)實(shí)時測量或在線估計目標(biāo)物體未知點(diǎn)的深度,提高了系統(tǒng)的控制性能。在微動機(jī)器人運(yùn)動學(xué)的基礎(chǔ)上建立了基于圖像的視覺伺服控制器,并對微操作閉環(huán)系統(tǒng)的穩(wěn)定性進(jìn)行了分析。針對顯微立體視覺伺服控制系統(tǒng)中穩(wěn)定性分析復(fù)雜的問題,本文建立了基于Hamilton理論的微定位控制算法。通過分解微動機(jī)器人的質(zhì)量矩陣,進(jìn)行了微操作系統(tǒng)動力學(xué)方程的模型變換。進(jìn)而將顯微立體視覺伺服控制系統(tǒng)實(shí)現(xiàn)為一類廣義Hamilton系統(tǒng)。設(shè)計了顯微視覺伺服控制器,使得微操作機(jī)器人閉環(huán)系統(tǒng)漸近穩(wěn)定。針對傳統(tǒng)的基于圖像的視覺伺服方法多采用物體的幾何特征如點(diǎn)、線、區(qū)域面積等作為特征值進(jìn)行視覺伺服控制時需要圖像處理過程中特征值的提取、匹配和跟蹤等問題,本文基于Phong照明模式和光流法提出了顯微立體視覺系統(tǒng)的微定位方法。此方法是以整幅圖像的像素亮度信息作為特征值進(jìn)行微操作系統(tǒng)的視覺反饋,進(jìn)而設(shè)計了基于亮度的直接伺服控制器,采用此方法避免了圖像處理過程中的特征值提取、匹配和跟蹤步驟。
[Abstract]:Micromanipulation is called micromanipulation on objects of characteristic size of micron and submicron magnitude, such as adsorption, capture, transfer, assembly and injection. Instruments that perform micromanipulation are called microoperating systems or micromanipulators. In recent years, microoperating systems have been widely used in MEMS (Micro Electro Mechanical System), microelectro-mechanical systems (MOEMS (Micro Opto Electro Mechanical System) and bio-MEMS systems (Bio MEMS (Biological Micro Electro Mechanical System). The micro vision servo control system, which combines the micro manipulation robot system with the micro vision information, has the ability of intelligent interaction with the external environment, which is the main direction of the research and development of the micro operation robot system. At present, the research scope of microoperating system has developed from theoretical research to application design. Therefore, one of the future hotspots in the field of microoperating system is to apply it to industrial production on a large scale. In order to achieve this goal, the level and quality of microoperating system automation and intelligence will play a key role in the development process. In this paper, a complete micro stereo vision servo micro positioning control system is constructed by the overall planning of the system around the automation of the micro operating system. The system includes: end actuator module, motion control module and micro vision module. On the basis of this, the imaging model of micro stereo vision servo and the micro positioning control of the system are studied emphatically. Aiming at the problem of obtaining depth information in micro vision servo system, the imaging model of stereoscopic microscope SLM (Stereo Light Microscopy) with G (Greenough) and CMO (Common Main Objective) structure is established based on microscopic vision module in this paper. By using these two visual models, the visual information of objects can be directly obtained from 3D scenes, which avoids the real-time measurement or on-line estimation of the unknown point depth of the target object by the microoperating system, and improves the control performance of the system. Based on the kinematics of micro-robot, a visual servo controller based on image is established, and the stability of micro-operation closed-loop system is analyzed. Aiming at the complex problem of stability analysis in microstereoscopic vision servo control system, a micro-positioning control algorithm based on Hamilton theory is established in this paper. By decomposing the mass matrix of the micro robot, the model transformation of the dynamic equation of the micro operating system is carried out. Furthermore, the micro stereo vision servo control system is realized as a kind of generalized Hamilton system. A micro-vision servo controller is designed to make the closed-loop system of micro-manipulators asymptotically stable. In traditional image-based visual servo methods, the geometric features of objects such as points, lines, and area areas are often used as feature values for visual servo control, which need to be extracted, matched and tracked in the process of image processing. In this paper, based on Phong illumination mode and optical flow method, a micro positioning method for micro stereo vision system is proposed. In this method, the pixel luminance information of the whole image is used as the eigenvalue for the visual feedback of the micro-operating system, and then a direct servo controller based on brightness is designed, which avoids the extraction of the eigenvalue in the image processing process. Matching and tracking steps.
【學(xué)位授予單位】：燕山大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2015
【分類號】：TP316;TP242

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 趙瑋,于靖軍,畢樹生,宗光華;串并聯(lián)微操作機(jī)器人系統(tǒng)的研究[J];北京航空航天大學(xué)學(xué)報;2001年06期

2 黃心漢;;微裝配機(jī)器人系統(tǒng)研究與實(shí)現(xiàn)[J];華中科技大學(xué)學(xué)報(自然科學(xué)版);2011年S2期

3 趙清杰,連廣宇,孫增圻;機(jī)器人視覺伺服綜述[J];控制與決策;2001年06期

4 劉艷紅;李春文;王玉振;;基于Hamilton函數(shù)方法的多機(jī)多負(fù)荷電力系統(tǒng)分散勵磁控制(英文)[J];自動化學(xué)報;2009年07期

5 趙新;郭春艷;張瑋光;孫明竹;盧桂章;;基于顯微圖像處理的MEMS運(yùn)動測量方法[J];納米技術(shù)與精密工程;2012年01期

相關(guān)博士學(xué)位論文 前1條

1 于保軍;基于顯微視覺的微操作系統(tǒng)及其伺服控制研究[D];吉林大學(xué);2008年

，

本文編號：2290475