沈阳航空航天大学学报2026，Vol.43Issue(3)：61-68,8.DOI:10.3969/j.issn.2095-1248.2026.03.008
基于轮式里程计辅助视觉的无人车重定位算法
Relocalization algorithm for unmanned vehicles based on wheel odometry assisted vision
摘要
Abstract
To address the issue of SLAM-based visual relocalization failure in unmanned vehicles under visual degradation conditions,an adaptive collaborative relocalization algorithm was proposed,which combined wheel odometry(WO)with visual odometry(VO).This algorithm constructed a WO/VO fusion model based on error-state Kalman filter(ES-KF),enhancing the positioning accuracy of the unmanned vehicle's path planning.To tackle the challenge of insufficient visual feature points that hinder relocalization during unmaned vehicle operation,an adaptive collaborative relocalization algorithm for WO/VO was proposed.The system included a switching mechanism between WO/VO and WO,improving the continuity of the unmanned vehicle's localization and the reliability of path planning.Experiments were conducted and compared on the developed unmanned vehicle platform under various conditions.The results demonstrate that the ES-KF-based WO/VO fusion method significantly improves localization performance.The absolute trajectory error(ATE)is reduced by 39.1%and 59.2%,respectively,compared to VO-only and WO-only methods,and path overlap is increased by 9.2%and 11.5%,respectively.The algorithm also successfully achieves WO-assisted adaptive collaborative relocalization in visual degradation scenarios.Compared to the extended Kalman filter(EKF)and the unscented Kalman filter(UKF),the ES-KF demonstrates superior performance in both trajectory accuracy and pose estimation stability,significantly enhancing path fusion effectiveness and system robustness.关键词
重定位/视觉里程计/轮式里程计/无人车/误差状态卡尔曼滤波Key words
relocalization/visual odometry/wheel odometry/unmanned vehicle/error-state Kalman filter分类
信息技术与安全科学引用本文复制引用
曲萍萍,于浩楠,于腾丽,陈云浩,周忠鸿,霍文强,王尔申..基于轮式里程计辅助视觉的无人车重定位算法[J].沈阳航空航天大学学报,2026,43(3):61-68,8.基金项目
国家自然科学基金(项目编号:62173237) （项目编号:62173237）
云南省无人自主系统重点实验室开放课题(项目编号:202501ZD02). （项目编号:202501ZD02）
