In recent years there have been excellent results in Visual-Inertial Odometry
techniques, which aim to compute the incremental motion of the sensor with high
accuracy and robustness. However these approaches lack the capability to close
loops, and trajectory estimation accumulates drift even if the sensor is
continually revisiting the same place. In this work we present a novel
tightly-coupled Visual-Inertial Simultaneous Localization and Mapping system
that is able to close loops and reuse its map to achieve zero-drift
localization in already mapped areas. While our approach can be applied to any
camera configuration, we address here the most general problem of a monocular
camera, with its well-known scale ambiguity. We also propose a novel IMU
initialization method, which computes the scale, the gravity direction, the
velocity, and gyroscope and accelerometer biases, in a few seconds with high
accuracy. We test our system in the 11 sequences of a recent micro-aerial
vehicle public dataset achieving a typical scale factor error of 1% and
centimeter precision. We compare to the state-of-the-art in visual-inertial
odometry in sequences with revisiting, proving the better accuracy of our
method due to map reuse and no drift accumulation.

本文介绍了一种新的紧密耦合的视觉惯性同时定位和建图系统，采用惯性测量单元进行初始测量，实现了零漂移定位，带有地图重用功能，并应用于单目相机的最一般问题。在微型飞行器公共数据集的 11 个序列中测试了该系统，证明了其比目前最先进的视觉惯性测量方法更为准确。