计算机工程与应用2025，Vol.61Issue(4)：339-348,10.DOI:10.3778/j.issn.1002-8331.2310-0092
面向动态环境的紧耦合视觉惯性SLAM改进算法
Improved Tightly-Coupled Visual-Inertial SLAM Algorithm for Dynamic Environment
摘要
Abstract
SLAM(simultaneous localization and mapping)is a key technology for unmanned vehicles to achieve autono-mous navigation and positioning.In response to the problem of low accuracy of traditional visual SLAM system in dynamic environment,inertial measurement unit(IMU)is imported.A visual-inertial SLAM system for dynamic environment is designed based on the ORB-SLAM3 system.A sparse optical flow method based on vector field consensus(VFC)is pro-posed to track the feature points and calculate the fundamental matrix between images.The dynamic probability of feature points is calculated by epipolar geometry constraints of optical flow and IMU.A united dynamic feature detection algo-rithm is proposed to calculate the dynamic probability of feature points,and feature points that dynamic probability is greater than threshold are removed.This algorithm achieves tight coupling of visual information and inertial information in the front-end of the SLAM system.The experimental test results on the datasets indicate that the improved visual-inertial SLAM algorithm has good performance.关键词
同时定位与地图创建(SLAM)/视觉惯性紧耦合/动态环境/向量场一致性/ORB-SLAM3Key words
simultaneous localization and mapping(SLAM)/visual-inertial tightly-coupled/dynamic environment/vector field consensus/ORB-SLAM3分类
信息技术与安全科学引用本文复制引用
郭瑞奇,修睿,孙勇,毛喆..面向动态环境的紧耦合视觉惯性SLAM改进算法[J].计算机工程与应用,2025,61(4):339-348,10.基金项目
国家重点研发计划"智能传感器"重点专项(2022YFB3205005). （2022YFB3205005）
