【摘要】：隨著工業(yè)自動(dòng)化的飛速發(fā)展，機(jī)器人分揀技術(shù)被普遍地應(yīng)用在各類生產(chǎn)線上。傳統(tǒng)的機(jī)器人分揀大多采用示教方式，對(duì)機(jī)器人的初始和終止姿態(tài)及工件的擺放位置有嚴(yán)格的要求，這樣不但分揀速度慢、效率低，而且一旦工件位置發(fā)生變化則會(huì)導(dǎo)致機(jī)器人抓取失敗，從而影響生產(chǎn)效率。于是，人們把視線轉(zhuǎn)移到機(jī)器視覺領(lǐng)域，將視覺技術(shù)與機(jī)器人相結(jié)合，使機(jī)器人擁有類似人眼的識(shí)別功能，從而使機(jī)器人分揀時(shí)更加柔性化、高精化、智能化，對(duì)于降低勞動(dòng)成本、保證產(chǎn)品質(zhì)量、提高生產(chǎn)效率等方面具有重要意義。如今，機(jī)器視覺技術(shù)已經(jīng)被廣泛地應(yīng)用在無損檢測(cè)、食品包裝、醫(yī)藥生產(chǎn)、物流分揀、PCB制圖等諸多領(lǐng)域，基于視覺系統(tǒng)引導(dǎo)的機(jī)器人技術(shù)也將成為未來發(fā)展的主要趨勢(shì)。 本文針對(duì)從生產(chǎn)線上的雜亂工件堆中分揀出目標(biāo)工件，提出了一種基于模板匹配的工件視覺識(shí)別算法，并以新松公司RH6-A型6軸工業(yè)機(jī)器人為基礎(chǔ)，搭建了基于機(jī)器視覺的工業(yè)機(jī)器人分揀系統(tǒng)，制定了詳細(xì)的視覺分揀的方案。本文首先進(jìn)行了工業(yè)機(jī)器人運(yùn)動(dòng)學(xué)分析，應(yīng)用D-H坐標(biāo)變換法求出了運(yùn)動(dòng)學(xué)正解及反變換法解出反解，并根據(jù)該算法開發(fā)了基于OpenGL的機(jī)器人仿真系統(tǒng)。其次分析了OpenCV視覺算法庫中提供的攝像機(jī)模型，并采用張正友標(biāo)定法進(jìn)行了攝像機(jī)標(biāo)定，建立了機(jī)器人手眼關(guān)系，求解出攝像機(jī)內(nèi)、外參數(shù)及變換矩陣。然后通過工業(yè)相機(jī)采集工件圖像，，對(duì)采集到的圖像進(jìn)行平滑、去噪等預(yù)處理，以消除圖像中摻雜的噪聲，再利用Sobel邊緣算子對(duì)工件進(jìn)行邊緣檢測(cè)，得到工件的邊緣信息，接著進(jìn)行圖像二值化處理，最后利用Hausdorff距離算法對(duì)模板圖像和待匹配圖像進(jìn)行相似性度量，完成模板匹配。 實(shí)驗(yàn)結(jié)果表明，基于邊緣的模板匹配算法成功地識(shí)別匹配出了雜亂工件中的目標(biāo)工件，然后通過圖像的中心矩計(jì)算出了工件的中心坐標(biāo)，并將特征信息反饋給機(jī)器人控制器，達(dá)到機(jī)器人分揀工件的目的。
[Abstract]:With the rapid development of industrial automation, robot sorting technology is widely used in various production lines. The traditional robot sorting mostly adopts the teaching method, which has strict requirements on the initial and terminating posture of the robot and the placement position of the workpiece, so that the sorting speed is slow and the efficiency is low. And once the position of the workpiece changes, it will lead to the failure of the robot grab, thus affecting the production efficiency. Therefore, people turn their sight to the field of machine vision, combine vision technology with robot, so that robot has the recognition function similar to human eye, so that the robot can be more flexible, highly refined and intelligent when sorting. It is of great significance to reduce labor cost, guarantee product quality and improve production efficiency. Nowadays, machine vision technology has been widely used in many fields such as nondestructive testing, food packaging, pharmaceutical production, logistics sorting, PCB drawing and so on. Robot technology based on vision system will also become the main trend of future development. In this paper, a visual recognition algorithm of workpiece based on template matching is proposed, which is based on RH6- A-6 axis industrial robot of Xinsong Company, aiming at sorting out the target workpiece from the cluttered workpiece heap on the production line. An industrial robot sorting system based on machine vision is built, and a detailed visual sorting scheme is formulated. In this paper, the kinematics of industrial robot is analyzed firstly, and the forward and inverse kinematics solutions are obtained by using DH coordinate transformation method. According to this algorithm, the robot simulation system based on OpenGL is developed. Secondly, the camera model provided in the OpenCV vision algorithm library is analyzed, and the camera calibration is carried out by using Zhang Zhengyou calibration method. The hand-eye relationship of the robot is established, and the inner and outer parameters of the camera and the transformation matrix are solved. Then the image of the workpiece is collected by the industrial camera, and the collected image is smoothed and de-noised, so as to eliminate the doping noise in the image. Then, the edge information of the workpiece is obtained by using the Sobel edge operator to detect the edge of the workpiece. Then the binary image processing is carried out. Finally, the Hausdorff distance algorithm is used to measure the similarity between the template image and the image to be matched to complete the template matching. The experimental results show that the edge-based template matching algorithm successfully recognizes and matches the target workpiece in the clutter workpiece, then calculates the center coordinates of the workpiece through the central moment of the image, and feeds the feature information back to the robot controller. To achieve the purpose of robot sorting workpiece.
【學(xué)位授予單位】：沈陽工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP391.41;TP242

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