Rapid And Robust Monocular Visual-Inertial Initialization With Gravity Estimation Via Vertical Edges

2019 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)(2019)

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摘要
Monocular visual-inertial tracking without good initialization easily fails due to its non-linear nature. Rapid and accurate metric initialization is crucial. In this paper, we propose a novel monocular visual-inertial initialization method which can initialize the IMU states, camera poses, and scale in a rapid and robust way. To avoid mixing gravity and accelerometer bias, we propose to use the detected vertical edges to estimate a better gravity. This improves the observability to the underlying problem even without sufficient movement, so we can solve all the states crucial for a good initialization. We evaluate our approach on EuRoC dataset and compare with existing state-of-the-art methods. The experimental results demonstrate the effectiveness of the proposed method.
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关键词
monocular visual-inertial tracking,IMU states,detected vertical edges,robust monocular visual-inertial initialization,gravity estimation,metric initialization,camera poses,EuRoC dataset
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