西安工程大学学报2025，Vol.39Issue(2)：19-27,9.DOI:10.13338/j.issn.1674-649x.2025.02.003
单目视觉移动机器人高精度鲁棒定位方法
High-precision and robust positioning method for monocular vision mobile robot
摘要
Abstract
When mobile robots use monocular vision sensors for simultaneous localization and mapping(SLAM),they encounter numerous challenges in complex environments characterized by frequent lighting changes and sparse environmental textures,leading to inaccuracies in positio-ning.Therefore,this article focuses on improving the front-end and positioning components of the ORB-SLAM3 system to enhance the accuracy and robustness of monocular vision mobile robots.Firstly,we proposed a regional dynamic feature probability threshold adjustment algorithm to en-hance the SuperPoint network,replacing the original ORB algorithm for image feature extraction.This step was aimed to acquire more robust and evenly distributed visual feature points.Second-ly,we introduced a common view matching strategy and dynamic window matching strategy,opti-mizing the feature matching and tracking algorithm of the visual front-end.This optimization sig-nificantly improved visual tracking performance in scenes with sparse textures.Finally,by combi-ning the proposed improved algorithm with multi-sensor information fusion technology,a com-plete positioning system framework was constructed.An experiment was conducted using this system.The results demonstrate that the improved algorithm reduces the absolute trajectory er-ror on the EuRoc dataset by 8.6%compared to ORB-SLAM3.In a real-world environment,the error of the robot is reduced by 33.59%compared to that before the improvement.关键词
移动机器人/同步定位与建图(SLAM)/ORB-SLAM3/SuperPoint/单目视觉Key words
mobile robot/simultaneous localization and mapping(SLAM)/ORB-SLAM3/Su-perPoint/monocular vision分类
计算机与自动化引用本文复制引用
王晓华,邓越,王雪玉,陈伟重..单目视觉移动机器人高精度鲁棒定位方法[J].西安工程大学学报,2025,39(2):19-27,9.基金项目
陕西省自然科学基金项目(2024JC-YBQN-0671) （2024JC-YBQN-0671）
碑林区应用技术研发储备工程项目(GX2306) （GX2306）
