{"title":"多功能机器人感知系统实现闭环控制,实现大型部件涂胶过程的零缺陷制造","authors":"Loukas Prezas, Zoi Arkouli, George Michalos, Panagiotis Angelakis, Christos Gkournelos, Sotiris Makris","doi":"10.1016/j.robot.2024.104778","DOIUrl":null,"url":null,"abstract":"<div><p>Significant progress has been made in robot perception facilitating the deployment of advanced automation across a wide range of applications however typically little solutions are presented for large parts manufacturing. This paper presents a versatile robot perception system designed to enhance the flexibility and precision of robotic adhesive dispensing processes. This solution is capable of addressing the unique challenges of implementing automation solutions in large parts manufacturing, such as flexibility to manufacture small lot sizes, perception for complex task sequences, and handling parts with large dimensions that cannot be captured in single camera frames. A solution based on one single vision sensor is presented for part type recognition, part localization, process monitoring, and quality inspection. This includes algorithms for these perception functionalities and a closed-loop control framework aimed at zero-defect manufacturing. The task planning and execution architecture is based on Behavior Trees to allow modular and scalable robot task modeling and execution, whereas a knowledge database updated with process monitoring results via a module named event manager serves to prevent the propagation of defects to the following production steps. The proposed approach was tested and validated in a robotic cell for glue dispensing for a case study inspired by the bus and coach sector. The results indicate that the system can tolerate position uncertainties and random parts feeding, address disruptions in-process or trigger corrective actions post-process, and easily accommodate new variants.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"181 ","pages":"Article 104778"},"PeriodicalIF":4.3000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multi-purpose robot perception system enabling closed-loop control for zero defect manufacturing in gluing processes of large parts\",\"authors\":\"Loukas Prezas, Zoi Arkouli, George Michalos, Panagiotis Angelakis, Christos Gkournelos, Sotiris Makris\",\"doi\":\"10.1016/j.robot.2024.104778\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Significant progress has been made in robot perception facilitating the deployment of advanced automation across a wide range of applications however typically little solutions are presented for large parts manufacturing. This paper presents a versatile robot perception system designed to enhance the flexibility and precision of robotic adhesive dispensing processes. This solution is capable of addressing the unique challenges of implementing automation solutions in large parts manufacturing, such as flexibility to manufacture small lot sizes, perception for complex task sequences, and handling parts with large dimensions that cannot be captured in single camera frames. A solution based on one single vision sensor is presented for part type recognition, part localization, process monitoring, and quality inspection. This includes algorithms for these perception functionalities and a closed-loop control framework aimed at zero-defect manufacturing. The task planning and execution architecture is based on Behavior Trees to allow modular and scalable robot task modeling and execution, whereas a knowledge database updated with process monitoring results via a module named event manager serves to prevent the propagation of defects to the following production steps. The proposed approach was tested and validated in a robotic cell for glue dispensing for a case study inspired by the bus and coach sector. The results indicate that the system can tolerate position uncertainties and random parts feeding, address disruptions in-process or trigger corrective actions post-process, and easily accommodate new variants.</p></div>\",\"PeriodicalId\":49592,\"journal\":{\"name\":\"Robotics and Autonomous Systems\",\"volume\":\"181 \",\"pages\":\"Article 104778\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Robotics and Autonomous Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0921889024001623\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Autonomous Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921889024001623","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
A multi-purpose robot perception system enabling closed-loop control for zero defect manufacturing in gluing processes of large parts
Significant progress has been made in robot perception facilitating the deployment of advanced automation across a wide range of applications however typically little solutions are presented for large parts manufacturing. This paper presents a versatile robot perception system designed to enhance the flexibility and precision of robotic adhesive dispensing processes. This solution is capable of addressing the unique challenges of implementing automation solutions in large parts manufacturing, such as flexibility to manufacture small lot sizes, perception for complex task sequences, and handling parts with large dimensions that cannot be captured in single camera frames. A solution based on one single vision sensor is presented for part type recognition, part localization, process monitoring, and quality inspection. This includes algorithms for these perception functionalities and a closed-loop control framework aimed at zero-defect manufacturing. The task planning and execution architecture is based on Behavior Trees to allow modular and scalable robot task modeling and execution, whereas a knowledge database updated with process monitoring results via a module named event manager serves to prevent the propagation of defects to the following production steps. The proposed approach was tested and validated in a robotic cell for glue dispensing for a case study inspired by the bus and coach sector. The results indicate that the system can tolerate position uncertainties and random parts feeding, address disruptions in-process or trigger corrective actions post-process, and easily accommodate new variants.
期刊介绍:
Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems.
Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.