{"title":"3D guiding assisted augmented assembly technology with rapid object detection in dynamic environment","authors":"","doi":"10.1016/j.aei.2024.102857","DOIUrl":null,"url":null,"abstract":"<div><div>In the field of industrial assembly, augmented reality (AR) technology has played an important role and demonstrated its enormous development potential in the future. With the current development of product assembly towards customization and diversification, it is difficult to meet the requirements of augmented assembly (AA) by relying on static instructions registered with markers. However, most augmented assembly guidance systems used for dynamic environments are complex, cumbersome, and exhibit high latency, significantly impacting the user experience. In addition, the narrow field of view (Fov) of AR glasses also limits its further application in industrial scene. In response to the above issues, this article proposes an improved 3D guiding assisted augmented assembly technology. Firstly, a lightweight model Yolov7-Slim is proposed to achieve object detection on 2D images, which reduces File size by 26.7 % and improves running speed by 15.3 % compared to the Yolov7-tiny model. Secondly, a 3D positioning algorithm is proposed to achieve the rapid conversion of 2D coordinates to 3D coordinates. Finally, a user-oriented two-stage guidance mechanism is designed to compensate for the limitation of the narrow Fov of AR glasses. To quantify the performance of proposed technology, a 3D guiding assisted augmented assembly system (3DG3AS) was developed and validated in a reducer assembly experiment.</div></div>","PeriodicalId":50941,"journal":{"name":"Advanced Engineering Informatics","volume":null,"pages":null},"PeriodicalIF":8.0000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Engineering Informatics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1474034624005056","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
In the field of industrial assembly, augmented reality (AR) technology has played an important role and demonstrated its enormous development potential in the future. With the current development of product assembly towards customization and diversification, it is difficult to meet the requirements of augmented assembly (AA) by relying on static instructions registered with markers. However, most augmented assembly guidance systems used for dynamic environments are complex, cumbersome, and exhibit high latency, significantly impacting the user experience. In addition, the narrow field of view (Fov) of AR glasses also limits its further application in industrial scene. In response to the above issues, this article proposes an improved 3D guiding assisted augmented assembly technology. Firstly, a lightweight model Yolov7-Slim is proposed to achieve object detection on 2D images, which reduces File size by 26.7 % and improves running speed by 15.3 % compared to the Yolov7-tiny model. Secondly, a 3D positioning algorithm is proposed to achieve the rapid conversion of 2D coordinates to 3D coordinates. Finally, a user-oriented two-stage guidance mechanism is designed to compensate for the limitation of the narrow Fov of AR glasses. To quantify the performance of proposed technology, a 3D guiding assisted augmented assembly system (3DG3AS) was developed and validated in a reducer assembly experiment.
期刊介绍:
Advanced Engineering Informatics is an international Journal that solicits research papers with an emphasis on 'knowledge' and 'engineering applications'. The Journal seeks original papers that report progress in applying methods of engineering informatics. These papers should have engineering relevance and help provide a scientific base for more reliable, spontaneous, and creative engineering decision-making. Additionally, papers should demonstrate the science of supporting knowledge-intensive engineering tasks and validate the generality, power, and scalability of new methods through rigorous evaluation, preferably both qualitatively and quantitatively. Abstracting and indexing for Advanced Engineering Informatics include Science Citation Index Expanded, Scopus and INSPEC.