納米操作機(jī)視覺(jué)伺服技術(shù)研究
發(fā)布時(shí)間：2018-11-18 07:29
【摘要】：納米技術(shù)在飛速發(fā)展,納米材料依靠其優(yōu)良獨(dú)特的性能應(yīng)用于各個(gè)領(lǐng)域。納米操作技術(shù)對(duì)納米科技的發(fā)展起到至關(guān)重要的作用。以往的納米操作系統(tǒng)都是依靠人手工操作信號(hào)輸入設(shè)備完成對(duì)納米器件的操作,這種方法很費(fèi)時(shí),還容易造成設(shè)備損壞。隨著機(jī)器人技術(shù)的快速發(fā)展,實(shí)現(xiàn)納米操作的自動(dòng)化是大勢(shì)所趨。納米操作的自動(dòng)化必須實(shí)現(xiàn)閉環(huán)控制,然而現(xiàn)有的傳感器很難達(dá)到納米級(jí)別的測(cè)量精度,掃描電子顯微鏡(SEM)憑借其極高的分辨率、高采樣率成為納米操作系統(tǒng)發(fā)展必不可少的工具。本文提出依靠掃描電鏡圖像,利用視覺(jué)伺服技術(shù)實(shí)現(xiàn)一定程度上自動(dòng)化的納米操作機(jī),總結(jié)了用于納米操作機(jī)的視覺(jué)伺服技術(shù)并對(duì)這些方法在納米操作機(jī)上的應(yīng)用效果進(jìn)行了仿真測(cè)試。首先搭建了納米操作系統(tǒng),分析了各組成部分的作用。選擇SEM作為視覺(jué)伺服系統(tǒng)圖像信息采集反饋裝置,簡(jiǎn)要介紹了掃描電鏡的成像原理和系統(tǒng)選用電鏡的型號(hào)和性能指標(biāo);選擇壓電陶瓷驅(qū)動(dòng)器作為探針控制器件,得到壓電陶瓷器件的簡(jiǎn)化模型;同時(shí)為了實(shí)現(xiàn)系統(tǒng)的快速性,在位置反饋環(huán)節(jié)依靠掃描電鏡和應(yīng)變片共同完成。由于整個(gè)系統(tǒng)性能很大程度上依賴(lài)于SEM圖像,需要對(duì)圖像進(jìn)行高性能處理,包括降噪和圖像漂移補(bǔ)償。選擇NL-means算法作為去噪濾波器,相對(duì)于傳統(tǒng)的降噪方法有更優(yōu)良的性能;但這種方法運(yùn)算量大,普通的處理方式不能滿(mǎn)足伺服系統(tǒng)的實(shí)時(shí)性要求,隨后采用依靠GPU并行加速的方法解決去噪的快速性問(wèn)題;提出了將圖像相似性算法用于對(duì)SEM圖像漂移補(bǔ)償?shù)姆桨?作為實(shí)現(xiàn)視覺(jué)伺服的必備條件,必須知道被控對(duì)象和目標(biāo)的實(shí)時(shí)位置,本文利用具有仿射不變性的SIFT算法實(shí)現(xiàn)對(duì)探針針尖的運(yùn)動(dòng),對(duì)于追蹤目標(biāo)的辨識(shí),依據(jù)具體使用條件做出調(diào)整。課題的目標(biāo)是通過(guò)SEM圖像獲得壓電驅(qū)動(dòng)器所需的輸入信號(hào),由圖像信息作為控制規(guī)律的輸入信號(hào)得到。將小孔成像模型的雅可比模型遷移到SEM成像模型上,依靠在線(xiàn)調(diào)節(jié)算法獲得實(shí)時(shí)圖像雅可比矩陣;針對(duì)探針控制快速性和精確性的綜合要求,實(shí)現(xiàn)基于應(yīng)變片信號(hào)和基于視覺(jué)伺服的信號(hào)切換方法;提出一種簡(jiǎn)單而實(shí)用性強(qiáng)的Z軸接觸檢測(cè)方法。最后,在圖像平面上進(jìn)行了目標(biāo)跟蹤仿真,并對(duì)仿真結(jié)果做出分析,從而得到最優(yōu)的控制參數(shù);利用VRML軟件搭建起三維笛卡爾坐標(biāo)系下的視覺(jué)伺服控制仿真平臺(tái),模擬了視覺(jué)伺服的實(shí)現(xiàn)過(guò)程。
[Abstract]:Nanotechnology is developing rapidly. Nanomaterials are applied in various fields depending on their excellent and unique properties. Nanotechnology plays an important role in the development of nanotechnology. In the past, the nanoscale operating system used to rely on human manual operation signal input equipment to complete the operation of nano-devices, this method is time-consuming, but also easy to cause damage to the device. With the rapid development of robot technology, it is the trend of the times to realize the automation of nano-operation. The automation of nanoscale operation must be controlled by closed loop. However, it is very difficult for the existing sensors to achieve the measurement accuracy of nanometer level. The scanning electron microscope (SEM) has its very high resolution. High sampling rate has become an essential tool for the development of nanoscale operating systems. In this paper, we propose to realize a certain degree of automation of nanoscale manipulators by means of scanning electron microscope images and visual servo technology. In this paper, the visual servo technology used in nano manipulators is summarized, and the application effect of these methods in nano manipulators is tested by simulation. First, the nanometer operating system is built, and the function of each component is analyzed. SEM is selected as the image information collection and feedback device of the visual servo system. The imaging principle of the scanning electron microscope and the model and performance index of the system are briefly introduced. The piezoelectric actuator is selected as the probe controller to obtain the simplified model of the piezoelectric ceramic device, and in order to realize the rapidity of the system, the scanning electron microscope and strain gauge are used to achieve the position feedback. Since the performance of the whole system depends heavily on SEM images, it is necessary to perform high performance image processing, including noise reduction and image drift compensation. The NL-means algorithm is chosen as the denoising filter, which has better performance than the traditional de-noising method. However, this method can not meet the real-time requirement of servo system because of its large computation, and then it adopts the method of parallel acceleration of GPU to solve the problem of fast de-noising. An image similarity algorithm is proposed to compensate SEM image drift. As a necessary condition to realize visual servo, we must know the real time position of the controlled object and the target. In this paper, we use the affine invariant SIFT algorithm to realize the motion of the probe tip and identify the tracking target. Make adjustment according to specific use condition. The object of this paper is to obtain the input signal of piezoelectric actuator by SEM image, which is obtained by image information as the input signal of control law. The Jacobian model of the pinhole imaging model is migrated to the SEM imaging model, and the real time image Jacobian matrix is obtained by on-line adjusting algorithm. Aiming at the comprehensive requirement of the speed and accuracy of probe control, the method of signal switching based on strain gauge signal and visual servo is realized, and a simple and practical Z-axis contact detection method is proposed. Finally, the target tracking simulation is carried out on the image plane, and the simulation results are analyzed to obtain the optimal control parameters. The visual servo control simulation platform in 3D Cartesian coordinate system is built by using VRML software, and the realization process of visual servo is simulated.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TB383.1;TP391.41
本文編號(hào)：2339319
[Abstract]:Nanotechnology is developing rapidly. Nanomaterials are applied in various fields depending on their excellent and unique properties. Nanotechnology plays an important role in the development of nanotechnology. In the past, the nanoscale operating system used to rely on human manual operation signal input equipment to complete the operation of nano-devices, this method is time-consuming, but also easy to cause damage to the device. With the rapid development of robot technology, it is the trend of the times to realize the automation of nano-operation. The automation of nanoscale operation must be controlled by closed loop. However, it is very difficult for the existing sensors to achieve the measurement accuracy of nanometer level. The scanning electron microscope (SEM) has its very high resolution. High sampling rate has become an essential tool for the development of nanoscale operating systems. In this paper, we propose to realize a certain degree of automation of nanoscale manipulators by means of scanning electron microscope images and visual servo technology. In this paper, the visual servo technology used in nano manipulators is summarized, and the application effect of these methods in nano manipulators is tested by simulation. First, the nanometer operating system is built, and the function of each component is analyzed. SEM is selected as the image information collection and feedback device of the visual servo system. The imaging principle of the scanning electron microscope and the model and performance index of the system are briefly introduced. The piezoelectric actuator is selected as the probe controller to obtain the simplified model of the piezoelectric ceramic device, and in order to realize the rapidity of the system, the scanning electron microscope and strain gauge are used to achieve the position feedback. Since the performance of the whole system depends heavily on SEM images, it is necessary to perform high performance image processing, including noise reduction and image drift compensation. The NL-means algorithm is chosen as the denoising filter, which has better performance than the traditional de-noising method. However, this method can not meet the real-time requirement of servo system because of its large computation, and then it adopts the method of parallel acceleration of GPU to solve the problem of fast de-noising. An image similarity algorithm is proposed to compensate SEM image drift. As a necessary condition to realize visual servo, we must know the real time position of the controlled object and the target. In this paper, we use the affine invariant SIFT algorithm to realize the motion of the probe tip and identify the tracking target. Make adjustment according to specific use condition. The object of this paper is to obtain the input signal of piezoelectric actuator by SEM image, which is obtained by image information as the input signal of control law. The Jacobian model of the pinhole imaging model is migrated to the SEM imaging model, and the real time image Jacobian matrix is obtained by on-line adjusting algorithm. Aiming at the comprehensive requirement of the speed and accuracy of probe control, the method of signal switching based on strain gauge signal and visual servo is realized, and a simple and practical Z-axis contact detection method is proposed. Finally, the target tracking simulation is carried out on the image plane, and the simulation results are analyzed to obtain the optimal control parameters. The visual servo control simulation platform in 3D Cartesian coordinate system is built by using VRML software, and the realization process of visual servo is simulated.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類(lèi)號(hào)】：TB383.1;TP391.41
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