{"title":"研制一种能够确定物体角度的智能机械臂抓取与控制系统","authors":"Nian-Ze Hu, Qiuping Lin, Ruo-Wei Wu, You-Xing Zeng, Bo-An Lin, Shang-Wei Liu, Kai-Hsun Hsu, Jeng-Dao Lee, Ying-Hsiu Hung, Chun-Min Tsai","doi":"10.1109/ECICE55674.2022.10042951","DOIUrl":null,"url":null,"abstract":"The automatic judgment of the object’s angle can enhance the work efficiency of mechanical loading and unloading, which is necessary for the workflow of non-fixed placement. Therefore, we develop a method for judging object angles that can be imported into various scenarios. First of all, the model of each tool is established. Before the identification process, the proposed system improves the accuracy by adjusting the brightness and contrast. Then, the position and angle of the object are judged to command the robotic arm for gripping. In addition, the best gripping point is found according to the boundary shape of the object to enhance the stability of the moving process so that the workpiece does not fall during the process. The object’s coordinates, angle, and clamping position are determined after the images are captured through the camera to improve the efficiency of the handling process. This design can be implemented in various loading and unloading processes.","PeriodicalId":282635,"journal":{"name":"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Develop an Intelligent Robotic Arm Grasp and Control System Capable of Determining the Angle of Objects\",\"authors\":\"Nian-Ze Hu, Qiuping Lin, Ruo-Wei Wu, You-Xing Zeng, Bo-An Lin, Shang-Wei Liu, Kai-Hsun Hsu, Jeng-Dao Lee, Ying-Hsiu Hung, Chun-Min Tsai\",\"doi\":\"10.1109/ECICE55674.2022.10042951\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The automatic judgment of the object’s angle can enhance the work efficiency of mechanical loading and unloading, which is necessary for the workflow of non-fixed placement. Therefore, we develop a method for judging object angles that can be imported into various scenarios. First of all, the model of each tool is established. Before the identification process, the proposed system improves the accuracy by adjusting the brightness and contrast. Then, the position and angle of the object are judged to command the robotic arm for gripping. In addition, the best gripping point is found according to the boundary shape of the object to enhance the stability of the moving process so that the workpiece does not fall during the process. The object’s coordinates, angle, and clamping position are determined after the images are captured through the camera to improve the efficiency of the handling process. This design can be implemented in various loading and unloading processes.\",\"PeriodicalId\":282635,\"journal\":{\"name\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECICE55674.2022.10042951\",\"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 IEEE 4th Eurasia Conference on IOT, Communication and Engineering (ECICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECICE55674.2022.10042951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Develop an Intelligent Robotic Arm Grasp and Control System Capable of Determining the Angle of Objects
The automatic judgment of the object’s angle can enhance the work efficiency of mechanical loading and unloading, which is necessary for the workflow of non-fixed placement. Therefore, we develop a method for judging object angles that can be imported into various scenarios. First of all, the model of each tool is established. Before the identification process, the proposed system improves the accuracy by adjusting the brightness and contrast. Then, the position and angle of the object are judged to command the robotic arm for gripping. In addition, the best gripping point is found according to the boundary shape of the object to enhance the stability of the moving process so that the workpiece does not fall during the process. The object’s coordinates, angle, and clamping position are determined after the images are captured through the camera to improve the efficiency of the handling process. This design can be implemented in various loading and unloading processes.