湖南大学学报（自然科学版）2026，Vol.53Issue(4)：10-18,9.DOI:10.16339/j.cnki.hdxbzkb.2026262
基于语义拓扑信息的物体级SLAM回环检测算法
Loop closure detection method with semantic topology information for object SLAM
摘要
Abstract
Loop closure detection is a crucial component of SLAM systems,enabling the elimination of accumulated odometry errors.Traditional appearance-based methods face challenges in handling large viewpoint changes.This paper proposes a visual loop closure detection method based on semantic topological information.By leveraging the viewpoint invariance of object landmarks and encoding scenes through an object-oriented semantic topological map,the method significantly enhances system robustness under large viewpoint changes.Specifically,the method maintains a hierarchical semantic landmark database and adopts a"coarse-to-fine"detection strategy.First,high-level macroscopic object landmarks are utilized to extract topological graphs for coarse matching via local topological descriptors;to effectively eliminate mismatches,local and global topological graphs are unified in a polar coordinate system to evaluate spatial distribution similarity.Subsequently,guided by accurate object matches,fine registration is performed using low-level microscopic point landmarks to optimize pose estimation.Experimental results on the TUM and USTC datasets demonstrate that the proposed method exhibits superior performance in both precision and recall,achieving an average precision of over 80%.Notably,in large-disparity loop closure scenarios,positioning accuracy is improved by more than 40%.关键词
机器人技术/物体级SLAM/回环检测/语义分割/语义地图Key words
robotics/object SLAM/loop closure detection/semantic segmentation/semantic mapping分类
信息技术与安全科学引用本文复制引用
徐彪,曾聪磊,张润邦,黄圣杰,刘硕,秦晓辉,王若钦..基于语义拓扑信息的物体级SLAM回环检测算法[J].湖南大学学报（自然科学版）,2026,53(4):10-18,9.基金项目
长三角科技创新共同体联合攻关计划项目(2023 CSJGG0801),Yangtze River Delta Science and Technology Innovation Joint Force(2023CSJGG0801) （2023 CSJGG0801）
