机电工程技术2026，Vol.55Issue(8)：90-95,158,7.DOI:10.3969/j.issn.1009-9492.2026.08.016
面向动态环境的前后端协同视觉惯性SLAM研究分析
Collaborative Front-end and Back-end Visual-inertial SLAM for Dynamic Environments
摘要
Abstract
Traditional visual-inertial SLAM systems suffer from degraded positioning and poor robustness in dynamic scenes,as the static-world assumption is no longer valid.To address this problem,a collaborative front-end/back-end VI-SLAM approach is proposed that explicitly handles moving features.At the front end,a probabilistic identification framework based on motion consistency is introduced.By comparing the observed parallax angle with the pre-integrated value from the inertial measurement unit(IMU)and combining first-order temporal filtering,smooth and continuous dynamic confidence values are generated for each feature point.Features with high confidence are treated as likely moving and are either removed early or softly down-weighted.In the back end,an adaptive robust optimizer fused with the prior dynamic confidence is designed.The probabilities prior information from the front end is introduced into the weighted bundle adjustment(BA)under the framework of the adaptive truncated least-squares(ATLS)cost fuction,so that staged weighting suppresses and dynamic outliers are realized.Experiments conducted on the VIODE(Visual-Inertial Odometry in Dynamic Environments)dataset show that,compared to DynaVINS,the proposed method reduces the ATE(Absolute Trajectory Error)RMSE(Root Mean Square Error)by 29.0%and 38.6%on the high-dynamic sequences city_day_high and parking_lot_high,respectively.Furthermore,as the degree of dynamics increases,the performance of this method degrades more gradually,demonstrating superior robustness.The experimental results confirm that the proposed method can effectively enhance the accuracy and reliability of VI-SLAM systems in complex dynamic environments.关键词
视觉惯性SLAM/动态场景/光束法平差/视差角/运动一致性Key words
visual-inertial SLAM/dynamic environments/bundle adjustment/parallax angle/motion consistency分类
信息技术与安全科学引用本文复制引用
朱新宇,詹宇成,陈诗亮,孙雅茹..面向动态环境的前后端协同视觉惯性SLAM研究分析[J].机电工程技术,2026,55(8):90-95,158,7.基金项目
四川省民航飞行技术与飞行安全工程技术研究中心其他实验室开放课题(GY2024_23D) （GY2024_23D）
