1. 上海大学 通信与信息工程学院,上海,200444
2. 上海先进通信与数据科学研究院,上海,200444
纸质出版:2021
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成坚炼, 韩军, 张国强. 基于半直接法视觉里程计的单目视觉惯性系统[J]. 微电子学与计算机, 2021, 38(4): 35-39.
CHENG Jian-lian, HAN Jun, ZHANG Guo-qiang. Monocular visual inertial system based on semi-direct visual odometry[J]. 2021, 38(4): 35-39.
针对单目视觉系统姿态估计精度不高的问题,提出了一种基于半直接法视觉里程计(SVO)的单目视觉惯性系统.系统使用误差状态卡尔曼滤波器以松耦合方式对视觉信息和惯性导航信息进行融合.视觉前端采用SVO处理图像数据,并修改了SVO的关键帧选择策略以及解决了相机前视场景中由于重定位失败导致姿态估计失败的问题.使用EuRoc数据集中的MH 01子集对所提算法进行验证.实验表明,基于SVO的单目视觉惯性系统能够有效的提高姿态估计精度.相比单目SVO算法,所提算法的位置误差减少了13.4%
旋转角的误差减少了30%.
Aiming at the problem of low attitude estimation accuracy of monocular visual system
a monocular visual inertial system based on semi-direct visual odometry (SVO) is proposed. The system uses an error-state Kalman filter to fuse visual information and inertial navigation information in a loosely coupled manner. SVO is used to process image data in the visual front-end
and the SVO keyframe selection strategy is modified to solve the problem of attitude estimation failure due to relocation failure in the front-view scene of the camera. The proposed algorithm is validated by using the MH 01 subset of the EuRoc dataset. The experiment shows that the monocular visual inertial system based on the SVO can effectively improve the accuracy of attitude estimation. Compared with the monocular SVO algorithm
the position error of the proposed algorithm is reduced by 13.4%
the error of the rotation angle is reduced by 30%.
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