本文選題：庫卡工業(yè)機器人 + 機器視覺��； 參考：《深圳大學》2017年碩士論文

【摘要】：隨著工業(yè)機器人技術(shù)在生產(chǎn)制造領域的廣泛應用,越來越多的工業(yè)機器人被應用到制造領域,代替人工完成對生產(chǎn)線上物料的分揀。雖然通過對工業(yè)機器人示教編程可以完成分揀任務,但是往往對周邊設備要求較高,并且成本也較高。對于多目標,工件的形狀、尺寸和擺放位置不確定的分揀任務,如何讓機器人完成工件的識別和定位,并準確的抓取目標是使分揀機器人更加智能化的關鍵。將機器視覺技術(shù)運用到工業(yè)機器人當中,使機器人具有人眼的功能,通過視覺引導使工業(yè)機器人完成對目標的抓取具有重要意義。1本文對庫卡KR 6 R700 sixx工業(yè)機器人進行了視覺分揀技術(shù)研究。單個工業(yè)機器人不能定位分揀工作平面上物料的位置,為了使機器人能確定物料的位置,基于圖像傳感技術(shù)設計了視覺識別、定位方法,實現(xiàn)了機器視覺定位。將機器視覺技術(shù)運用于庫卡工業(yè)機器人使機器人確定目標物料的位置。建立了工業(yè)機器人的連桿坐標系,根據(jù)連桿坐標系確定了D-H參數(shù)表,建立了機器人的運動學方程,并求解了庫卡工業(yè)機器人的正逆解。采用五次多項式曲線對庫卡機器人進行了關節(jié)空間的軌跡規(guī)劃。利用正運動學解,采用隨機數(shù)的方法分析了機器人的工作空間。工業(yè)攝像機作為分揀機器人的圖像傳感器。分析了視覺系統(tǒng)中的四個坐標系,并分析了工業(yè)攝像機的線性成像模型和非線性成像模型。研究了基于平面靶標的工業(yè)攝像機標定方法,構(gòu)建了工業(yè)攝像機的標定實驗,獲得了工業(yè)攝像機的內(nèi)外參數(shù)矩陣。在分揀工作平面上的18cm×18cm區(qū)域進行了視覺定位實驗,分析了視覺定位誤差。最大定位誤差小于0.9mm。工業(yè)攝像機獲取工件的圖像后,采用雙邊濾波器對圖像進行濾波,采用了大津法閾值分割方法提取工件圖像。提取了工件的輪廓,通過判斷輪廓的面積來完成對工件的識別。通過提取輪廓的中心獲得了工件的像素位置。設計了角度計算方法獲取工件的角度信息。分析PC與庫卡工業(yè)機器人的位姿數(shù)據(jù)通信,確定了通信數(shù)據(jù)的字符串格式。通過搭建PC端數(shù)據(jù)發(fā)送服務器實現(xiàn)了PC與機器人的數(shù)據(jù)通信。最后搭建了視覺分揀系統(tǒng)并進行分揀實驗。實驗結(jié)果表明,庫卡KR 6 R700 sixx工業(yè)機器人能夠完成對目標工件的視覺分揀,提高了分揀機器人的自適應性。
[Abstract]:With the wide application of industrial robot technology in the field of production and manufacture, more and more industrial robots have been applied to the field of manufacturing, instead of manually completing the sorting of materials on the production line. Although the sorting task can be accomplished by instructing the industrial robot, it often requires high peripheral equipment and high cost. How to make the robot complete the identification and localization of the work piece and grasp the target accurately is the key to make the sorting robot more intelligent for the task of sorting the multi-target, the shape, the size and the position of the work piece which is uncertain. The application of machine vision technology to industrial robots, so that the robot has the function of the human eye, It is of great significance to make the industrial robot complete the target capture through visual guidance. In this paper, the visual sorting technology of KR6 R700 sixx industrial robot is studied. A single industrial robot can not locate the position of the material in the sorting work plane. In order to make the robot determine the position of the material, a vision recognition and location method is designed based on the image sensing technology, and the machine vision positioning is realized. The machine vision technology is applied to the Kuka industrial robot to determine the position of the target material. The connecting rod coordinate system of the industrial robot is established, the D-H parameter table is determined according to the connecting rod coordinate system, the kinematics equation of the robot is established, and the forward and inverse solutions of the Kuka industrial robot are solved. The joint space trajectory planning of Kuka robot is carried out by using the polynomial curve of the fifth degree. Using the positive kinematics solution, the workspace of the robot is analyzed by the method of random number. Industrial cameras are used as image sensors for sorting robots. Four coordinate systems in the vision system are analyzed, and the linear and nonlinear imaging models of industrial cameras are analyzed. The calibration method of industrial camera based on planar target is studied. The calibration experiment of industrial camera is constructed and the internal and external parameter matrix of industrial camera is obtained. The visual localization experiment was carried out in the 18cm 脳 18cm area of the sorting work plane, and the visual positioning error was analyzed. The maximum positioning error is less than 0.9mm. After the industrial camera acquires the image of the workpiece, the two-sided filter is used to filter the image, and the threshold segmentation method is used to extract the image of the workpiece. The contour of the workpiece is extracted, and the recognition of the workpiece is completed by judging the area of the contour. The pixel position of the workpiece is obtained by extracting the center of the contour. The angle calculation method is designed to obtain the angle information of the workpiece. The data communication between PC and Kuka industrial robot is analyzed, and the string format of communication data is determined. The data communication between PC and robot is realized by building PC data sending server. Finally, the visual sorting system is built and the sorting experiment is carried out. The experimental results show that the KR6 R700 sixx industrial robot can achieve the visual sorting of the target workpiece and improve the self-adaptability of the sorting robot.
【學位授予單位】：深圳大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41;TP242.2

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