CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
FMD Stereo SLAM: Fusing MVG and Direct Formulation Towards Accurate and Fast Stereo SLAM
Tang, Fulin1,2; Li, Heping1,2; Wu, Yihong1,2
2019-05
Conference NameInternational Conference on Robotics and Automation
Conference Date2019年5月20日-2019年5月24日
Conference PlaceMontreal, Canada
Abstract

We propose a novel stereo visual SLAM framework considering both accuracy and speed at the same time. The framework makes full use of the advantages of key-featurebased multiple view geometry (MVG) and direct-based formulation. At the front-end, our system performs direct formulation and constant motion model to predict a robust initial pose,
reprojects local map to find 3D-2D correspondence and finally refines pose by the reprojection error minimization. This frontend process makes our system faster. At the back-end, MVG is used to estimate 3D structure. When a new keyframe is inserted, new mappoints are generated by triangulating. In order to improve the accuracy of the proposed system, bad mappoints are removed and a global map is kept by bundle adjustment. Especially, the stereo constraint is performed to optimize the map. This back-end process makes our system more accurate. Experimental evaluation on EuRoC dataset shows that the proposed algorithm can run at more than 100 frames per second on a consumer computer while achieving highly competitive accuracy.

Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/39188
Collection模式识别国家重点实验室_机器人视觉
Corresponding AuthorWu, Yihong
Affiliation1.中国科学院自动化研究所
2.中国科学院大学
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Tang, Fulin,Li, Heping,Wu, Yihong. FMD Stereo SLAM: Fusing MVG and Direct Formulation Towards Accurate and Fast Stereo SLAM[C],2019.
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