Yurou Chen, Ji-yang Yu, Liancheng Shen, Zhenyang Lin, Zhiyong Liu
{"title":"Vision-Based High-Precision Assembly with Force Feedback","authors":"Yurou Chen, Ji-yang Yu, Liancheng Shen, Zhenyang Lin, Zhiyong Liu","doi":"10.1109/ICCAR57134.2023.10151762","DOIUrl":null,"url":null,"abstract":"Assembling objects in unstructured scenarios re-quires accurate 3D position estimation, which presents a sig-nificant challenge in achieving high-precision manipulation. This paper proposes a method to reduce positioning errors in high-precision assembly problems by combining visual and force feedback. Our approach leverages the strengths of both sensors by analyzing visual positioning characteristics and using force feedback to locate the target position during inaccuracies. We evaluate our approach through experiments of inserting a nut onto a screw without threading, conducted in both simulation and real-world scenarios. Our results demonstrate an improvement in the assembly success rate compared to previous methods.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAR57134.2023.10151762","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Assembling objects in unstructured scenarios re-quires accurate 3D position estimation, which presents a sig-nificant challenge in achieving high-precision manipulation. This paper proposes a method to reduce positioning errors in high-precision assembly problems by combining visual and force feedback. Our approach leverages the strengths of both sensors by analyzing visual positioning characteristics and using force feedback to locate the target position during inaccuracies. We evaluate our approach through experiments of inserting a nut onto a screw without threading, conducted in both simulation and real-world scenarios. Our results demonstrate an improvement in the assembly success rate compared to previous methods.