{"title":"灵活制造机械手系统的敏捷视觉感知和控制算法","authors":"Kang Yuan, Xuegang Zhang, Li Yan, Hao Liu","doi":"10.1109/ROBIO58561.2023.10354578","DOIUrl":null,"url":null,"abstract":"The manipulator systems with vision perception play an import role in intelligent manufacturing, helping to achieve industrial automation production. However, the electronics manufacturing industry, especially in scenarios such as consumer electronics manufacturing, has a strong demand for flexible manufacturing. The traditional calibration methods for vision perception require manual operation, customized calibration objects and their world-frame coordinates, which cannot meet the requirements of flexible production. Therefore, a novel agile vision calibration, perception and control algorithm is designed to meet flexible manufacturing requirements in the paper. The proposed algorithm receives vision pixel raw information as unique input, derives calibration matrix and manipulator control target pose automatically. The algorithm is adapted for both eye-in-hand and eye-on-hand vision sensor, and the theoretical analysis shows that the calibration algorithm has no manual operation errors. Experimental verification shows that the designed calibration algorithm in this article is simpler to operate, has fewer sources of error, easier to control, and has higher calibration accuracy than traditional calibration algorithms, while meeting the requirements of flexible manufacturing.","PeriodicalId":505134,"journal":{"name":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","volume":"72 12","pages":"1-8"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Agile Vision Perception and Control Algorithm for Flexible Manufacturing Manipulator System\",\"authors\":\"Kang Yuan, Xuegang Zhang, Li Yan, Hao Liu\",\"doi\":\"10.1109/ROBIO58561.2023.10354578\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The manipulator systems with vision perception play an import role in intelligent manufacturing, helping to achieve industrial automation production. However, the electronics manufacturing industry, especially in scenarios such as consumer electronics manufacturing, has a strong demand for flexible manufacturing. The traditional calibration methods for vision perception require manual operation, customized calibration objects and their world-frame coordinates, which cannot meet the requirements of flexible production. Therefore, a novel agile vision calibration, perception and control algorithm is designed to meet flexible manufacturing requirements in the paper. The proposed algorithm receives vision pixel raw information as unique input, derives calibration matrix and manipulator control target pose automatically. The algorithm is adapted for both eye-in-hand and eye-on-hand vision sensor, and the theoretical analysis shows that the calibration algorithm has no manual operation errors. Experimental verification shows that the designed calibration algorithm in this article is simpler to operate, has fewer sources of error, easier to control, and has higher calibration accuracy than traditional calibration algorithms, while meeting the requirements of flexible manufacturing.\",\"PeriodicalId\":505134,\"journal\":{\"name\":\"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)\",\"volume\":\"72 12\",\"pages\":\"1-8\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROBIO58561.2023.10354578\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE International Conference on Robotics and Biomimetics (ROBIO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROBIO58561.2023.10354578","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Agile Vision Perception and Control Algorithm for Flexible Manufacturing Manipulator System
The manipulator systems with vision perception play an import role in intelligent manufacturing, helping to achieve industrial automation production. However, the electronics manufacturing industry, especially in scenarios such as consumer electronics manufacturing, has a strong demand for flexible manufacturing. The traditional calibration methods for vision perception require manual operation, customized calibration objects and their world-frame coordinates, which cannot meet the requirements of flexible production. Therefore, a novel agile vision calibration, perception and control algorithm is designed to meet flexible manufacturing requirements in the paper. The proposed algorithm receives vision pixel raw information as unique input, derives calibration matrix and manipulator control target pose automatically. The algorithm is adapted for both eye-in-hand and eye-on-hand vision sensor, and the theoretical analysis shows that the calibration algorithm has no manual operation errors. Experimental verification shows that the designed calibration algorithm in this article is simpler to operate, has fewer sources of error, easier to control, and has higher calibration accuracy than traditional calibration algorithms, while meeting the requirements of flexible manufacturing.