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状态估计器

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VINS-Mono: A Robust and Versatile Monocular Visual-

Inertial State Estimator

Shaozu Cao, Jie Pan, Jieqi Shi and Shaojie Shen

Hong Kong University of Science and Technology

{shaozu.cao, jpanai, jshias, eeshaojie}@connect.ust.hk

I. Original Framework

Our system is based on the VINS-MONO[1] framework illustrated in the picture.

We first extract features from images provided by a camera sensor and operate

optical flow algorithms to complete a pre-treatment. Meanwhile, we do IMU pre-

integration between two consecutive frames. After pre-processing everything we need,

we perform a robust estimator initialization.

In the initialization procedure, we make use of visual structure from motion

together with visual-inertial alignment. This loosely-coupled sensor fusion method

offers us initial values we need to build a monocular tightly-coupled visual-inertial

system.

To change from loosely to tightly coupled, we proceed with a sliding window-

based optimization system for high accuracy and robust state estimation. We also

employ marginalization to bound the computational complexity of our optimization-

based VIO. What’s more, a lightweight motion-only visual-inertial BA is carried out to

boost the estimation.

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