{"title":"用直线检测方法寻找贴标机的拾取点","authors":"Lipheng Prum, Rutchanee Gullayanon, John Morris","doi":"10.1109/ICSEC56337.2022.10049335","DOIUrl":null,"url":null,"abstract":"We developed a new technique for detecting the position of labels using a SCARA Robot with the end-effector vacuum pad. The technique first found the image edge with a Canny detector, then selected straight lines and their intersections. It assumed that the label was basically rectangular in shape and roughly aligned so that the key edges were close to horizontal and vertical directions. The slope of the horizontal edge defined the rotational of the label. Otherwise, reducing the image tilting and the distortion by using a perspective transform matrix and thereafter converting the image coordinate into the SCARA robot coordinate. Through the factory environment, the experiment is conducted using various captured image conditions under a lighting source. The performance of the system provides the acceptable accuracy all of the picking coordinates with positioning errors, which x-coordinate are 0.01 – 0.25 mm, y-coordinate are 0.01 – 0.32 mm and rotation angle are 0.05° – 3.94°. In trials, the SCARA robot was able to grip the label precisely in each test.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Finding Picking Point Using Straight Line Detection of Label Attachment Machine\",\"authors\":\"Lipheng Prum, Rutchanee Gullayanon, John Morris\",\"doi\":\"10.1109/ICSEC56337.2022.10049335\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We developed a new technique for detecting the position of labels using a SCARA Robot with the end-effector vacuum pad. The technique first found the image edge with a Canny detector, then selected straight lines and their intersections. It assumed that the label was basically rectangular in shape and roughly aligned so that the key edges were close to horizontal and vertical directions. The slope of the horizontal edge defined the rotational of the label. Otherwise, reducing the image tilting and the distortion by using a perspective transform matrix and thereafter converting the image coordinate into the SCARA robot coordinate. Through the factory environment, the experiment is conducted using various captured image conditions under a lighting source. The performance of the system provides the acceptable accuracy all of the picking coordinates with positioning errors, which x-coordinate are 0.01 – 0.25 mm, y-coordinate are 0.01 – 0.32 mm and rotation angle are 0.05° – 3.94°. In trials, the SCARA robot was able to grip the label precisely in each test.\",\"PeriodicalId\":430850,\"journal\":{\"name\":\"2022 26th International Computer Science and Engineering Conference (ICSEC)\",\"volume\":\"160 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 26th International Computer Science and Engineering Conference (ICSEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSEC56337.2022.10049335\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 26th International Computer Science and Engineering Conference (ICSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSEC56337.2022.10049335","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
我们开发了一种利用末端执行器真空垫的SCARA机器人检测标签位置的新技术。该方法首先利用Canny检测器找到图像边缘,然后选择直线及其交点。它假设标签的形状基本上是矩形的,并且大致对齐,以便关键边缘接近水平和垂直方向。水平边的斜率定义了标签的旋转。否则,通过透视变换矩阵将图像坐标转换为SCARA机器人坐标,减少图像的倾斜和畸变。通过工厂环境,在照明光源下使用各种捕获的图像条件进行实验。系统的性能可以满足所有具有定位误差的拾取坐标的可接受精度,其中x坐标为0.01 ~ 0.25 mm, y坐标为0.01 ~ 0.32 mm,旋转角度为0.05°~ 3.94°。在试验中,SCARA机器人在每次测试中都能准确地抓住标签。
Finding Picking Point Using Straight Line Detection of Label Attachment Machine
We developed a new technique for detecting the position of labels using a SCARA Robot with the end-effector vacuum pad. The technique first found the image edge with a Canny detector, then selected straight lines and their intersections. It assumed that the label was basically rectangular in shape and roughly aligned so that the key edges were close to horizontal and vertical directions. The slope of the horizontal edge defined the rotational of the label. Otherwise, reducing the image tilting and the distortion by using a perspective transform matrix and thereafter converting the image coordinate into the SCARA robot coordinate. Through the factory environment, the experiment is conducted using various captured image conditions under a lighting source. The performance of the system provides the acceptable accuracy all of the picking coordinates with positioning errors, which x-coordinate are 0.01 – 0.25 mm, y-coordinate are 0.01 – 0.32 mm and rotation angle are 0.05° – 3.94°. In trials, the SCARA robot was able to grip the label precisely in each test.