{"title":"基于b样条的手持LiDAR-SLAM设备轨迹估计","authors":"Xiangwei Zeng, Guojian He, Yan Zhuang","doi":"10.1109/IAI53119.2021.9619441","DOIUrl":null,"url":null,"abstract":"In this paper, a B-Spline-based trajectory estimation method is proposed and implemented based on the state-of-the-art LiDAR-SLAM framework LIOM. The proposed method parameterizes the trajectory with the cubic uniform B-Spline and performs a batch optimization within a local map to get LiDAR poses. Real-world experiments are conducted and the results demonstrate the high robustness and accuracy of the proposed method in challenging environments for handled LiDAR-SLAM applications.","PeriodicalId":106675,"journal":{"name":"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"B-Spline-Based Trajectory Estimation for Handheld LiDAR-SLAM Device\",\"authors\":\"Xiangwei Zeng, Guojian He, Yan Zhuang\",\"doi\":\"10.1109/IAI53119.2021.9619441\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a B-Spline-based trajectory estimation method is proposed and implemented based on the state-of-the-art LiDAR-SLAM framework LIOM. The proposed method parameterizes the trajectory with the cubic uniform B-Spline and performs a batch optimization within a local map to get LiDAR poses. Real-world experiments are conducted and the results demonstrate the high robustness and accuracy of the proposed method in challenging environments for handled LiDAR-SLAM applications.\",\"PeriodicalId\":106675,\"journal\":{\"name\":\"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)\",\"volume\":\"128 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IAI53119.2021.9619441\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 3rd International Conference on Industrial Artificial Intelligence (IAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI53119.2021.9619441","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
B-Spline-Based Trajectory Estimation for Handheld LiDAR-SLAM Device
In this paper, a B-Spline-based trajectory estimation method is proposed and implemented based on the state-of-the-art LiDAR-SLAM framework LIOM. The proposed method parameterizes the trajectory with the cubic uniform B-Spline and performs a batch optimization within a local map to get LiDAR poses. Real-world experiments are conducted and the results demonstrate the high robustness and accuracy of the proposed method in challenging environments for handled LiDAR-SLAM applications.