计算机与数字工程2026，Vol.54Issue(2)：333-337,360,6.DOI:10.3969/j.issn.1672-9722.2026.02.006
基于ORB-SLAM2算法的改进关键帧选择与稠密地图
Improved Keyframe Selection and Dense Map Based on ORB-SLAM2 Algorithm
陈伟 1高寒1
作者信息
- 1. 云南民族大学电气信息工程学院 昆明 650500
- 折叠
摘要
Abstract
Aiming at the problem of poor real-time performance and accuracy of the key frames selection method of the origi-nal ORB-SLAM2 algorithm,this paper proposes to improve the key frames selection method on the basis of the ORB-SLAM2 algo-rithm,while the traditional ORB-SLAM2 algorithm does not build a dense map and cannot meet the three-dimensional path plan-ning of the robot,so this paper proposes to add a dense point cloud map and a 3D Octomap construction thread on the basis of the original algorithm.The improved algorithm first limits the relative change between frames on the basis of the original algorithm to en-sure the matching accuracy between adjacent keyframes,then makes a comparison based on inliers,and finally sets the minimum feature change threshold to further process the keyframes,and constructs dense point cloud maps and 3D Octomap after eliminating redundant keyframes.Experimental results show that the positioning accuracy of the ORB-SLAM2 algorithm with improved key-frame selection on the TUM dataset is improved by about 24%on average compared with the original ORB-SLAM2 algorithm,and it can effectively construct dense point cloud maps and 3D Octomap in real time to meet the 3D path planning of robots.关键词
ORB-SLAM2/关键帧选择方法/稠密点云地图/3D Octomap/三维路径规划Key words
ORB-SLAM2/keyframe selection method/dense point cloud maps/3D Octomap/3D path planning分类
信息技术与安全科学引用本文复制引用
陈伟,高寒..基于ORB-SLAM2算法的改进关键帧选择与稠密地图[J].计算机与数字工程,2026,54(2):333-337,360,6.
