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二维卫星地图像素匹配的无人机视惯定位方法

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为提高无人机视觉惯性系统定位精度,提出了一种利用互联网二维卫星地图与无人机航拍图像匹配的视惯定位方法.首先通过航拍图像和惯性测量单元构建视觉惯性里程计(VIO),估计出无人机运动状态,获取特征点深度.然后对已匹配的图像对提取特征点,基于已知的卫星地图尺度和VIO估算的特征点深度进行像素级匹配和解算,获取匹配定位结果.最后构建VIO因子和匹配定位因子,采用因子图优化全局位姿.通过机载实验对所提方法进行验证,实验结果表明:相比于无地图匹配的VIO定位方法和无地图匹配的VIO+回环定位方法,所提方法的平均定位误差分别降低了50.14%和43.69%,有效提高了视觉惯性系统的定位精度.
UAV inertial location method based on pixel matching of 2D satellite maps
In order to improve the location accuracy of the unmanned aerial vehicle(UAV)visual inertial system,a visual inertial location method using Internet 2D satellite maps and UAV aerial images matching is proposed.Firstly,the aerial images and IMU are used to construct the visual inertial odometry(VIO)to estimate the UAV motion state and obtain the depth of feature points.Then extract feature points from the matched image pairs,perform pixel-level matching and solving based on the known satellite map scale and the depth of feature points estimated by VIO,and obtain the matching and location results.Finally,the VIO factor and the matching location factor are constructed,and the factor map is used to optimize the global position.The proposed method is validated by airborne experiments,and the experimental results show that the average location error is reduced by 50.14% compared with the VIO location method without map matching,and the average location error is reduced by 43.69% compared with the VIO and loopback location method without map matching.The location accuracy of the visual inertial system is effectively improved.

satellite mapsfeature matchingvisual inertial systemfactor maps

李磊磊、雷玉嵩、梅一林、吕文振、郝家镁、韩勇强

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北京理工大学 自动化学院,北京 100081

卫星地图 特征匹配 视惯系统 因子图

2024

中国惯性技术学报
中国惯性技术学会

中国惯性技术学报

CSTPCD北大核心
影响因子:0.792
ISSN:1005-6734
年,卷(期):2024.32(11)