【摘要】：在工業(yè)自動(dòng)化高速發(fā)展的背景下,越來越多的機(jī)器人技術(shù)被運(yùn)用于工業(yè)作業(yè)中,這當(dāng)中就包括機(jī)器人分揀技術(shù)。傳統(tǒng)的分揀技術(shù)往往使用運(yùn)動(dòng)示教方式,對(duì)于目標(biāo)位置要求必須固定,且有著較低的工作效率。將機(jī)器視覺與機(jī)械臂相結(jié)合,使得機(jī)械臂能夠自主地識(shí)別目標(biāo)物體,提高了作業(yè)速度,降低了勞力成本,有著重大的實(shí)際意義。機(jī)器人視覺技術(shù)使得機(jī)器人具備了視覺感知能力,如今也是當(dāng)今工業(yè)自動(dòng)化的重點(diǎn)研究領(lǐng)域。目前在工業(yè)上被廣泛用于缺陷檢測(cè)、物流、碼垛、焊接等眾多領(lǐng)域。本文以puma560機(jī)械臂為研究本體,對(duì)于基于位置的視覺伺服控制方法展開研究,設(shè)計(jì)了一個(gè)視覺分揀系統(tǒng)。將目標(biāo)工件圖像處理,工件的匹配識(shí)別,相機(jī)標(biāo)定,視覺控制器的設(shè)計(jì)為主線貫穿全文,最終實(shí)現(xiàn)了機(jī)械臂對(duì)于靜止目標(biāo)和運(yùn)動(dòng)目標(biāo)追蹤。本文重點(diǎn)針對(duì)以下幾點(diǎn)展開了研究:進(jìn)行了分揀目標(biāo)圖像處理算法的研究和設(shè)計(jì),通過實(shí)驗(yàn)對(duì)比選取了最佳的圖像處理方案,去除了目標(biāo)二值圖像的噪聲,得到了滿意的目標(biāo)二值圖。Otsu算法是圖像分割中最常用的方法之一,針對(duì)傳統(tǒng)Otsu算法需遍歷每個(gè)灰度值進(jìn)行類間方差的計(jì)算,本文提出一種快速的Otsu改進(jìn)算法,并與傳統(tǒng)算法進(jìn)行了比較,驗(yàn)證了新算法的有效性。對(duì)于分揀目標(biāo)進(jìn)行Harris角點(diǎn)特征提取,得到了模版和原圖像的角點(diǎn)特征圖像。并使用歸一化互相關(guān)(NCC)策略對(duì)原圖和模版圖進(jìn)行了粗匹配,得到了包含誤匹配的匹配結(jié)果。最終通過使用RANSAC策略去除了誤匹配,得到了提純后正確的匹配結(jié)果。進(jìn)行了視覺系統(tǒng)的標(biāo)定研究,分別對(duì)于相機(jī)標(biāo)定和手眼標(biāo)定方法進(jìn)行了理論研究與標(biāo)定實(shí)驗(yàn)。計(jì)算出了相機(jī)的內(nèi)外參數(shù),并給出了手眼矩陣求解一般方法。對(duì)于puma560進(jìn)行了運(yùn)動(dòng)學(xué)的求解,研究了基于位置的視覺伺服的控制方法。在matlab/simulink下進(jìn)行了視覺伺服的控制模型搭建,并分別實(shí)現(xiàn)了對(duì)靜止目標(biāo)定位以及運(yùn)動(dòng)目標(biāo)追蹤的仿真研究。通過上述的研究工作表明,本文提出的視覺系統(tǒng)方案對(duì)于目標(biāo)工件識(shí)別定位精度高,對(duì)于直線運(yùn)動(dòng)目標(biāo)追蹤效果好,證明了本文系統(tǒng)具有一定的實(shí)際意義。
[Abstract]:With the rapid development of industrial automation, more and more robot technologies are used in industrial operations, including robot sorting technology. The traditional sorting technology often uses the motion teaching method, which must be fixed for the target position, and has low working efficiency. It is of great practical significance to combine machine vision with robot arm to identify target objects independently, improve the working speed and reduce the labor cost. Robot vision technology makes robot have visual perception ability, and now it is the key research field of industrial automation. At present, it is widely used in many fields such as defect detection, logistics, palletizing, welding and so on. In this paper, the puma560 manipulator is taken as the research body, and a visual sorting system is designed based on the position based visual servo control method. The image processing, matching recognition, camera calibration and the design of vision controller are the main lines in the paper. Finally, the tracking of the stationary and moving targets by the manipulator is realized. This paper focuses on the following points: the research and design of sorting target image processing algorithm is carried out, the optimal image processing scheme is selected through experimental comparison, and the noise of the target binary image is removed. Otsu algorithm is one of the most commonly used methods in image segmentation. In view of the traditional Otsu algorithm needs to traverse each gray value to calculate the inter-class variance, a fast Otsu improved algorithm is proposed in this paper. Compared with the traditional algorithm, the validity of the new algorithm is verified. The corner feature images of template and original image are obtained by Harris corner feature extraction for sorting target. The normalized cross-correlation (NCC) strategy is used to match the original image and template map, and a matching result containing mismatch is obtained. Finally, the mismatch is removed by using RANSAC strategy, and the correct matching result is obtained after purification. The calibration of visual system is studied, and the methods of camera calibration and hand-eye calibration are studied and calibrated. The internal and external parameters of the camera are calculated, and the general method of hand-eye matrix solution is given. The kinematics of puma560 is solved, and the control method of visual servo based on position is studied. The control model of visual servo is built under matlab/simulink, and the simulation research of static target location and moving target tracking is realized respectively. The above research results show that the proposed vision system has high accuracy for target recognition and location, and good tracking effect for linear moving target, which proves that the proposed vision system has certain practical significance.
【學(xué)位授予單位】：西安建筑科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TP241

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