中山大学学报（自然科学版）（中英文）2026，Vol.65Issue(1)：23-32,10.DOI:10.11714/acta.snus.ZR20250210
室内复杂环境中LIO-SLAM算法的改进与优化
Improvement and optimization of LIO-SLAM algorithm in indoor complex environments
摘要
Abstract
This paper proposes an improved method that integrates visual odometry to address the defect of traditional LIO-SLAM being affected by sparse laser features and dynamic occlusion in complex indoor environments,resulting in decreased positioning accuracy.Specifically,while maintaining the LIO-SLAM laser inertial tight coupling framework,ORB-SLAM is introduced as an independent visual odometry module to provide high-frequency and rich texture visual constraint information for the system.By using an adaptive weight fusion strategy,multi-source optimization of laser,inertial,and visual observations is achieved,enhancing robustness in environments with weak geometric constraints and rich textures but complex structures.The experiment was conducted in various typical indoor scenarios(corridors,open halls,and dynamic crowd environments),and the results showed that the overall trajectory error was reduced to 70%of the original system,compared to the original LIO-SLAM.This study validates the feasibility and effectiveness of visual laser inertial multimodal fusion in complex indoor environments,providing new ideas for high-precision indoor autonomous positioning and map construction.关键词
室内自主定位/LIO-SLAM/ORB-SLAM/视觉里程计/多传感器融合Key words
indoor positioning/LIO-SLAM/ORB-SLAM/visual odometery/multi-sensor fusion分类
信息技术与安全科学引用本文复制引用
郝亮,陈国杰,胡肖彤,叶俊杰,王奇斌..室内复杂环境中LIO-SLAM算法的改进与优化[J].中山大学学报（自然科学版）（中英文）,2026,65(1):23-32,10.基金项目
中央高校基本业务费(ZYTS25049) （ZYTS25049）
