{"title":"Research and application of visual synchronous positioning and mapping technology assisted by ultra wideband positioning technology","authors":"Yiran Zhang, Lina Dong","doi":"10.1016/j.sasc.2025.200187","DOIUrl":null,"url":null,"abstract":"<div><div>With the development of the intelligent era, improving the positioning accuracy and operational stability of robots has become an urgent problem that needs to be solved. This study combines the advantages and disadvantages of visual synchronous positioning and mapping technology, inertial measurement units, and ultra-wideband technology to design a combined positioning system. The system first uses the pre-integration method of the inertial measurement unit to align the inertial measurement unit with the camera frequency. Then, it uses a tightly coupled method to fuse the measurement data of the system and the inertial measurement unit, forming a visual-inertial system. The study uses extended Kalman filtering to fuse the constructed visual-inertial system with ultra-wideband technology, creating an ultra-wideband/visual-inertial integrated system. Finally, simulation analysis was conducted on the constructed composite system. The results indicated that the RMSE of the ultra-wideband/visual-inertial system under light and dark conditions were 0.0123 and 0.0212, and 0.0114 and 0.0123, respectively, in the motion trajectories with and without forming a loop. In extremely complex motion trajectories, the RMSE error of the research system was 0.0123. This indicates that regardless of the conditions, the research system has long-term robustness and high-precision positioning performance.</div></div>","PeriodicalId":101205,"journal":{"name":"Systems and Soft Computing","volume":"7 ","pages":"Article 200187"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Systems and Soft Computing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772941925000055","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
With the development of the intelligent era, improving the positioning accuracy and operational stability of robots has become an urgent problem that needs to be solved. This study combines the advantages and disadvantages of visual synchronous positioning and mapping technology, inertial measurement units, and ultra-wideband technology to design a combined positioning system. The system first uses the pre-integration method of the inertial measurement unit to align the inertial measurement unit with the camera frequency. Then, it uses a tightly coupled method to fuse the measurement data of the system and the inertial measurement unit, forming a visual-inertial system. The study uses extended Kalman filtering to fuse the constructed visual-inertial system with ultra-wideband technology, creating an ultra-wideband/visual-inertial integrated system. Finally, simulation analysis was conducted on the constructed composite system. The results indicated that the RMSE of the ultra-wideband/visual-inertial system under light and dark conditions were 0.0123 and 0.0212, and 0.0114 and 0.0123, respectively, in the motion trajectories with and without forming a loop. In extremely complex motion trajectories, the RMSE error of the research system was 0.0123. This indicates that regardless of the conditions, the research system has long-term robustness and high-precision positioning performance.