兵工自动化2024，Vol.43Issue(5)：37-42,6.DOI:10.7690/bgzdh.2024.05.008
基于四叉树法和PROSAC算法改进的视觉SLAM技术
Improved Visual SLAM Technology Based on Quadtree Method and PROSAC Algorithm
杜根 1张志安1
作者信息
- 1. 南京理工大学机械工程学院,南京 210094
- 折叠
摘要
Abstract
In order to solve the problems of random sample consensus(RANSAC),such as high number of iterations,poor real-time performance and unstable robustness in the front end of simultaneous localization and mapping(SLAM),an improved image matching algorithm based on the fusion of quadtree method and progressive sample consensus(PROSAC)algorithm is proposed.The mismatching elimination algorithm of quadtree method+PROSAC algorithm is implemented,and the improved ORB-SLAM2 algorithm is tested on EuRoC data set.The results show that compared with ORB-SLAM2 system,the proposed algorithm reduces the average absolute trajectory error by 39.28%and the relative pose error by 35.45%on Vicon Room 1 03 dataset,and has higher mapping accuracy.关键词
四叉树编码/特征点匹配/PROSAC算法/SLAMKey words
quadtree coding/feature point matching/PROSAC algorithm/SLAM分类
信息技术与安全科学引用本文复制引用
杜根,张志安..基于四叉树法和PROSAC算法改进的视觉SLAM技术[J].兵工自动化,2024,43(5):37-42,6.
