计算机应用研究2024，Vol.41Issue(10)：3008-3014,7.DOI:10.19734/j.issn.1001-3695.2023.12.0636
基于点线特征融合的实时视惯SLAM算法
Real-time visual-inertial SLAM algorithm based on point-line feature fusion
摘要
Abstract
This paper introduced a real-time SLAM algorithm designed for mobile robots operating in environments characte-rized by low illumination and low texture.The algorithm leveraged the fusion of visual point-line features and IMU characteris-tics.It enhanced the EDlines algorithm by incorporating a leapfrog routing strategy and an adaptive threshold strategy,thereby improving the quality of line feature extraction and consequently enhancing feature tracking effectiveness.It established tight coupling constraints between visual and inertial features and employed a sliding window,along with a marginalization model,for nonlinear optimization.This enabled high-precision and real-time state estimation.Experimental results show that the proposed algorithm is superior effectiveness in online feature extraction when compared to traditional line segment extraction methods.Concurrently,the SLAM system achieves enhanced localization accuracy and robustness.关键词
视觉同步定位与建图/特征提取/视觉惯性紧耦合/滑动窗口Key words
visual simultaneous localization and mapping(VSLAM)/feature extraction/visual-inertial tight coupling/sliding window分类
计算机与自动化引用本文复制引用
王磊,陈帅坤,齐俊艳,袁瑞甫..基于点线特征融合的实时视惯SLAM算法[J].计算机应用研究,2024,41(10):3008-3014,7.基金项目
河南省科技创新团队资助项目(22IRTSTHN005) （22IRTSTHN005）
