高技术通讯2026，Vol.36Issue(6)：586-592,7.DOI:10.3772/j.issn.1002-0470.2026.06.004
基于语义分割的动态VSLAM建图线程实现
Realization of dynamic V-SLAM mapping thread based on semantic segmentation
摘要
Abstract
In order to solve the problems of redundant information and ghosting in map construction of traditional VSLAM in dynamic environments,a dynamic VSLAM mapping thread method based on DeepLabV3+is designed and ap-plied on ORB-SLAM3 architecture.Firstly,Key mapping frames are semantically segmented with a lightweight DeepLabV3+network to exclude dynamic regions.Secondly,the pose data after eliminating dynamic features is integrated with deep learning information,and then the point cloud map and octree map with semantic information are generated.Finally,the experimental results demonstrate that the maps constructed by the improved mapping method are with less redundant information and fewer ghosts which decrease the map space occupancy.关键词
视觉即时定位与地图构建/语义分割/DeepLabV3+网络/动态环境Key words
visual simultaneous localization and mapping/semantic segmentation/DeepLabV3+network/dynamic environment引用本文复制引用
黄卫华,张泽宇,章政..基于语义分割的动态VSLAM建图线程实现[J].高技术通讯,2026,36(6):586-592,7.基金项目
国家自然科学基金(62303359)资助项目. （62303359）
