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A Weighing Euler Pre-integration Method in the Visual-Inertial Odometry

机译:视觉惯性内径术中称重欧拉预集成方法

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Visual Inertial Odometry (VIO) has been widely used in many fields. Inertial Measurement Unit (IMU) pre-integration is an important part of data preprocessing throughout the VIO process. And improving the accuracy of pre-integration is of great significance for the subsequent joint initialization, motion estimation and optimization. This paper proposed a weighing Euler pre-integration method in a VIO, which is based on monocular camera and IMU. It weights the contiguous IMU data. Meanwhile, the influence of noise and biases are both discussed. In the monocular vision and inertial tightly coupled system, the experimental results proved to be ideal with the EuRoC MAV datasets, which can make better use of the angular velocity and acceleration measurements, and show a great improvement compared to the existing pre-integration technology.
机译:视觉惯性内径术(VIO)已广泛应用于许多领域。惯性测量单元(IMU)预集成是在整个VIO过程中预处理数据的重要组成部分。提高预整合的准确性对于随后的联合初始化,运动估计和优化具有重要意义。本文提出了一种基于单眼相机和IMU的VIO中称重欧拉预积分方法。它重量连续的IMU数据。同时,讨论了噪声和偏差的影响。在单眼视觉和惯性紧密耦合系统中,实验结果证明是欧盟的MAV数据集是理想的,这可以更好地利用角速度和加速度测量,并与现有的预集成技术相比显示出巨大的改进。

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