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Visual-Inertial Monocular SLAM with Map Reuse.pdf
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上传时间: 2020-04-06
详细说明：Abstract— 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 accumulatio
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