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

机译:视觉惯性里程表中的欧拉称重预积分方法

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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:视觉惯性里程表(VIO)已广泛应用于许多领域。惯性测量单元(IMU)的预集成是整个VIO流程中数据预处理的重要组成部分。而提高预积分的精度对后续关节的初始化,运动估计和优化具有重要意义。提出了一种基于单眼相机和IMU的VIO中的加权欧拉预积分方法。加权连续的IMU数据。同时,讨论了噪声和偏置的影响。在单眼视觉和惯性紧密耦合系统中,使用EuRoC MAV数据集证明了实验结果是理想的,该数据集可以更好地利用角速度和加速度测量值,并且与现有的预集成技术相比有很大的改进。

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