本文選題：安全套 + 機器人��； 參考：《沈陽工業(yè)大學(xué)》2017年碩士論文

【摘要】：自動上料機器人作為提高現(xiàn)代工業(yè)生產(chǎn)線自動化水平和解放生產(chǎn)力的有效途徑,將其引入到安全套電干檢環(huán)節(jié),將對實現(xiàn)安全套出廠檢測流程的自動化起到重要作用。機器視覺是當(dāng)下自動上料機器人的一個熱門研究領(lǐng)域,是自動上料機器人感知和獲取外部環(huán)境信息的重要途徑,同時也是指導(dǎo)自動上料機器人完成對物料的識別、定位、搬移等自主動作的關(guān)鍵技術(shù)。因此,本文將對安全套電干檢自動上料機器人的視覺定位系統(tǒng)進行研究,著重對以下四個方面進行闡述。首先,介紹了現(xiàn)有安全套主流檢測方法及電干檢機工作流程。針對電干檢機所存在的無法自動上料問題,提出了自動上料機器人+電干檢機的新型自動電干檢系統(tǒng)。其次,為了滿足自動上料機器人生產(chǎn)工藝所需的實時性、定位精度要求,需對安全套特征區(qū)域的識別與定位算法進行研究,結(jié)合該區(qū)域的邊界曲率特點,提出了一種預(yù)檢測+精檢測的兩步檢測算法和與之相匹配的形心定位算法。在預(yù)檢測階段,采用FAST算法中的Bresenham圓對已提取的安全套邊界點集進行曲率分類,根據(jù)邊界曲率趨勢篩選出特定的邊界點集并求出矩形掩膜區(qū)域。在精檢測階段,在矩形掩膜區(qū)域內(nèi)生成ORB特征算子和BRISK描述子。采用最近鄰域算法進行模板匹配,利用RANSAC算法剔除誤匹配。通過對預(yù)檢測后所提取邊界點集中的一點以其為中心做它的Bresenham圓鄰域,并以該圓鄰域與邊界的兩個交叉點的中點作為該區(qū)域的形心,以實現(xiàn)對安全套特征區(qū)域的形心定位。再次,在VS2013平臺上編寫基于Opencv2.4.13視覺庫的視覺定位軟件,該軟件融合了上述兩步檢測算法及形心定位算法,可以完成對于安全套的邊緣檢測、特征點檢測與匹配、特征區(qū)域形心定位,同時兼具攝像頭標(biāo)定、校準(zhǔn)以及通信功能。最后,將上述軟件與實驗裝置進行組裝和測試。結(jié)果表明,兩步算法能夠有效的規(guī)避在全局范圍內(nèi)進行費時的描述子生成過程,比單純的ORB+BRISK、BRISK等算法快5-8倍;同時繼承了ORB與BRISK算法的旋轉(zhuǎn)不變形和尺度不變性,提升了對安全套頂部區(qū)域形變時的識別與定位精度。以兩步檢測算法為核心編寫的視覺定位軟件滿足自動上料機器人的實際需求。
[Abstract]:As an effective way to improve the automation level and liberate the productivity of modern industrial production line, the automatic feeding robot will play an important role in the realization of the automation of condom testing process. Machine vision is a hot research field of automatic feeding robot at present. It is an important way for automatic feeding robot to perceive and obtain external environment information, and it is also a guide for automatic feeding robot to identify and locate materials. The key technology of autonomous movement, such as moving. Therefore, this paper will study the visual positioning system of the automatic feeding robot for electrical testing of condoms, focusing on the following four aspects. First of all, introduced the existing mainstream condom testing methods and electrical dry machine workflow. In order to solve the problem of automatic feeding of electric dry detector, a new type of automatic electric dry check system of automatic feeding robot is proposed. Secondly, in order to meet the requirements of real-time and positioning accuracy of automatic feeding robot, it is necessary to study the identification and location algorithm of condom feature area, combining with the boundary curvature characteristics of the region. A two-step detection algorithm and a matching centroid location algorithm are proposed. In the phase of pre-detection, the Bresenham circle of FAST algorithm is used to classify the extracted condom boundary points. According to the trend of boundary curvature, a specific set of boundary points is selected and the rectangular mask region is obtained. In the stage of fine detection, ORB feature operators and BRISK descriptors are generated in the rectangular mask region. The nearest neighborhood algorithm is used for template matching, and the RANSAC algorithm is used to eliminate the false matching. In order to realize the centroid orientation of condom characteristic region, the center of the two intersection points of the circle neighborhood and the boundary is taken as the center of the Bresenham circle neighborhood, and the center of the two intersection points of the circle neighborhood and the boundary is taken as the center of the point of the extracted boundary point set after the pre-detection. Thirdly, the visual location software based on Opencv2.4.13 vision library is written on VS2013 platform. The software combines the above two-step detection algorithm and centroid location algorithm, which can complete the edge detection, feature point detection and matching for condoms. Feature area centroid location, as well as camera calibration, calibration and communication functions. Finally, the software and the experimental device are assembled and tested. The results show that the two-step algorithm can effectively avoid the time-consuming descriptor generation process in the global scope, which is 5-8 times faster than the simple ORB BRISKBISK algorithm, and inherits the rotation invariance and scale invariance of the ORB and BRISK algorithms. Improved the identification and positioning accuracy of the top area deformation of condom. The visual positioning software based on the two-step detection algorithm can meet the practical requirements of the automatic feeding robot.
【學(xué)位授予單位】：沈陽工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41;TP242

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