湖南大学学报（自然科学版）2025，Vol.52Issue(12)：154-163,10.DOI:10.16339/j.cnki.hdxbzkb.2025277
鲁棒多层空间结构SLAM方法
Robust Multi-layer Spatial Structures SLAM
摘要
Abstract
In the simultaneous localization and mapping method of robots,the visual scheme has poor stability in indoor scenes with insufficient texture,and the use of structured assumptions can alleviate the above problems.However,if the indoor scene does not strictly meet the structured assumptions,it will lead to greater pose drift.More general structural assumptions and more reliable loopback detection methods can help solve the above problems and improve the robustness of indoor scene visual positioning.To this end,this paper proposes a robust multi-layer spatial structure assumption visual SLAM method.This method makes full use of the structured information in the scene,uses the main direction constraint to define the scene to assist the positioning,and uses a lightweight structured hypothesis loopback to reduce the cumulative drift,so as to construct a high robustness and low drift simultaneous localization mapping algorithm.We conduct a large number of experiments on real vehicle data and open source data sets.The experimental results show that the proposed method has higher positioning robustness and accuracy performance than other open source methods.The loopback detection method has a higher detection rate,and the positioning accuracy in the closed-loop scene is improved by 31.8%on average.关键词
机器人/同时定位与建图/结构化假设/主方向约束/回环检测/纹理Key words
robots/simultaneous localization and mapping/structured assumptions/main direction constraints/loopback detection/textures分类
信息技术与安全科学引用本文复制引用
秦洪懋,燕龙叶,黄圣杰,张润邦,郭瑾朋,周云水..鲁棒多层空间结构SLAM方法[J].湖南大学学报（自然科学版）,2025,52(12):154-163,10.基金项目
国家自然科学基金资助项目(52272415),National Natural Science Foundation of China(52272415) （52272415）
整车先进设计制造技术全国重点实验室项目(32315007、72275004),State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle(32315007、72275004) （32315007、72275004）
