Stereo Visual Inertial Odometry Using Incremental Smoothing

Visual inertial odometry (VIO) is a technique which estimates the motion of a mobile platform using the measurements from visual and inertial sensors. Recently, these sensors are made available with higher accuracy, smaller size, but lower cost thanks to the developing manufacturing of chips and mic...

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Bibliographic Details
Main Authors: Li, Yueliang, Zhong, Xunyu, Tian, Jun, Zou, Chaosheng, Peng, Xiafu
Format: Conference Proceeding
Language:English
Subjects:
Cameras
IMU pre-integration
incremental smoothing
Measurement uncertainty
motion estimation
Optimization
Robot vision systems
SLAM
stereo camera
Time measurement
Visual inertial odometry
Visualization
Online Access:Request full text
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Summary:Visual inertial odometry (VIO) is a technique which estimates the motion of a mobile platform using the measurements from visual and inertial sensors. Recently, these sensors are made available with higher accuracy, smaller size, but lower cost thanks to the developing manufacturing of chips and micro-electromechanical systems (MEMS) devices. However, it is very challenging for real-time visual inertial odometry to obtain robust and accurate localization and mapping with the limit of computational resources. In this paper, we present a stereo visual inertial odometry which pre-integrates IMU measurements to reduce the variables to be optimized and avoid repeated IMU integration during optimization. In addition, incremental smoothing is employed to obtain Maximum A Posteriori (MAP) estimates. The proposed method is shown to achieve high accuracy and efficiency in simulation results.
ISSN:2161-2927
DOI:10.23919/ChiCC.2018.8482677