本文關(guān)鍵詞： 視覺伺服 工業(yè)機(jī)器人 圖像處理 圖像雅可比矩陣　出處：《長春工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：機(jī)器人視覺伺服是機(jī)器視覺領(lǐng)域的熱門課題,涉及機(jī)器人學(xué)、控制理論、圖像處理等多門學(xué)科知識(shí)。視覺機(jī)器人具有自主分析環(huán)境信息和執(zhí)行任務(wù)的能力,廣泛應(yīng)用于航天、國防和工業(yè)自動(dòng)化領(lǐng)域。本文以六自由度工業(yè)機(jī)器人為研究對(duì)象,研究基于圖像的視覺伺服控制系統(tǒng),通過圖像采集獲取圖像信息后完成圖像處理,利用圖像特征作為反饋信號(hào),并對(duì)圖像雅可比矩陣進(jìn)行辨識(shí),利用辨識(shí)的結(jié)果應(yīng)用在視覺伺服控制器中,完成了MATLAB仿真和實(shí)驗(yàn)臺(tái)調(diào)試工作。主要研究內(nèi)容如下:首先,詳細(xì)分析了機(jī)器人視覺伺服控制系統(tǒng)的組成,闡述攝像機(jī)模型和機(jī)器人運(yùn)動(dòng)學(xué)分析,并對(duì)視覺伺服系統(tǒng)的類別進(jìn)行介紹,比較基于位置和圖像的視覺伺服系統(tǒng)。其次,對(duì)目標(biāo)圖像進(jìn)行圖像處理和分析,包括圖像采集、圖像預(yù)處理、圖像邊緣檢測(cè)和目標(biāo)特征提取。在預(yù)處理過程中高斯濾波方法對(duì)消除環(huán)境噪聲有著較好的效果。通過幾種圖像邊緣檢測(cè)方法對(duì)比分析,采用Canny邊緣檢測(cè)算子對(duì)圖像進(jìn)行邊緣檢測(cè),利用圖像矩的方法來對(duì)目標(biāo)特征進(jìn)行提取。再次,針對(duì)基于雅可比矩陣逆的視覺伺服控制方法進(jìn)行了研究。為了提高系統(tǒng)響應(yīng)的實(shí)時(shí)性,能對(duì)速度較快的目標(biāo)進(jìn)行有效的跟蹤,提出一種帶預(yù)測(cè)補(bǔ)償?shù)哪嫜趴杀染仃嘝I控制算法,并且采用擴(kuò)展H?粒子濾波算法對(duì)圖像雅可比矩陣進(jìn)行在線辨識(shí),與卡爾曼濾波算法進(jìn)行對(duì)比實(shí)驗(yàn)研究,仿真實(shí)驗(yàn)結(jié)果驗(yàn)證視覺伺服控制方法可行性。最后,構(gòu)建視覺伺服控制系統(tǒng)實(shí)驗(yàn)平臺(tái),完成了目標(biāo)識(shí)別和目標(biāo)跟蹤實(shí)驗(yàn)。采用C++來設(shè)計(jì)視覺伺服控制系統(tǒng)界面,通過對(duì)運(yùn)動(dòng)目標(biāo)的軌跡跟蹤實(shí)驗(yàn)驗(yàn)證了本文的控制方法在實(shí)際工程應(yīng)用中的有效性,實(shí)驗(yàn)結(jié)果表明基于圖像的視覺伺服系統(tǒng)能夠達(dá)到預(yù)定效果。
[Abstract]:Robot vision servo is a hot topic in the field of machine vision, involving robotics, control theory, image processing and other subjects. Visual robot has the ability to analyze environmental information and perform tasks independently, and it is widely used in spaceflight. In the field of national defense and industrial automation. In this paper, a visual servo control system based on image is studied, which takes six degrees of freedom industrial robot as the research object. The image feature is used as feedback signal, and the image Jacobian matrix is identified. The result of identification is applied to the visual servo controller. The MATLAB simulation and experiment bench debugging are completed. The main research contents are as follows: first, The composition of robot visual servo control system is analyzed in detail, the camera model and robot kinematics analysis are expounded, the categories of visual servo system are introduced, and the visual servo system based on position and image is compared. Secondly, Image processing and analysis of the target image, including image acquisition, image preprocessing, Image edge detection and target feature extraction. Gao Si filtering method has a good effect on eliminating environmental noise in the process of preprocessing. The comparison and analysis of several image edge detection methods, The Canny edge detection operator is used to detect the edge of the image, and the method of image moment is used to extract the target feature. The visual servo control method based on Jacobian matrix inverse is studied. In order to improve the real-time response of the system and to track the faster target effectively, an inverse Jacobian matrix Pi control algorithm with predictive compensation is proposed. And use extended H? The particle filter algorithm is used to identify the image Jacobian matrix online, and compared with the Kalman filter algorithm. The simulation results verify the feasibility of the visual servo control method. Finally, a visual servo control system experimental platform is constructed. The interface of visual servo control system is designed by using C, and the effectiveness of the control method in practical engineering is verified by the trajectory tracking experiment of moving target. Experimental results show that the image based visual servo system can achieve a predetermined effect.
【學(xué)位授予單位】：長春工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TP242

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