Liangliang Gao, Chaoyi Dong, Xiaoyang Liu, Qifan Ye, Kang Zhang, Xiaoyan Chen
{"title":"Improved 2D laser slam graph optimization based on Cholesky decomposition","authors":"Liangliang Gao, Chaoyi Dong, Xiaoyang Liu, Qifan Ye, Kang Zhang, Xiaoyan Chen","doi":"10.1109/CoDIT55151.2022.9803938","DOIUrl":null,"url":null,"abstract":"Laser slam usually needs to complete a back-end graph optimization at a fast speed in some specific scenes, such as sharp turns, fast motion, and limited calculation time. Aiming at these problems, this paper proposed a 2D laser slam back-end graph optimization combined with Cholesky decomposition to accelerate a linear solution process and further to achieve a purpose of accelerating graph optimization. In MATLAB simulation experiments, the rate of 2D laser slam back-end graph optimization combined with Cholesky decomposition increased 24%, compared to that of the traditional method without Cholesky decomposition. The result verified the effectiveness of the improved method.","PeriodicalId":185510,"journal":{"name":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 8th International Conference on Control, Decision and Information Technologies (CoDIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CoDIT55151.2022.9803938","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Laser slam usually needs to complete a back-end graph optimization at a fast speed in some specific scenes, such as sharp turns, fast motion, and limited calculation time. Aiming at these problems, this paper proposed a 2D laser slam back-end graph optimization combined with Cholesky decomposition to accelerate a linear solution process and further to achieve a purpose of accelerating graph optimization. In MATLAB simulation experiments, the rate of 2D laser slam back-end graph optimization combined with Cholesky decomposition increased 24%, compared to that of the traditional method without Cholesky decomposition. The result verified the effectiveness of the improved method.