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A progressive online external parameter calibration and initialization method for stereo-IMU system
Industrial Robot ( IF 1.8 ) Pub Date : 2021-12-02 , DOI: 10.1108/ir-07-2021-0135
Yanwu Zhai 1 , Haibo Feng 1 , Yili Fu 1
Affiliation  

Purpose

This paper aims to present a pipeline to progressively deal with the online external parameter calibration and estimator initialization of the Stereo-inertial measurement unit (IMU) system, which does not require any prior information and is suitable for system initialization in a variety of environments.

Design/methodology/approach

Before calibration and initialization, a modified stereo tracking method is adopted to obtain a motion pose, which provides prerequisites for the next three steps. Firstly, the authors align the pose obtained with the IMU measurements and linearly calculate the rough external parameters and gravity vector to provide initial values for the next optimization. Secondly, the authors fix the pose obtained by the vision and restore the external and inertial parameters of the system by optimizing the pre-integration of the IMU. Thirdly, the result of the previous step is used to perform visual-inertial joint optimization to further refine the external and inertial parameters.

Findings

The results of public data set experiments and actual experiments show that this method has better accuracy and robustness compared with the state of-the-art.

Originality/value

This method improves the accuracy of external parameters calibration and initialization and prevents the system from falling into a local minimum. Different from the traditional method of solving inertial navigation parameters separately, in this paper, all inertial navigation parameters are solved at one time, and the results of the previous step are used as the seed for the next optimization, and gradually solve the external inertial navigation parameters from coarse to fine, which avoids falling into a local minimum, reduces the number of iterations during optimization and improves the efficiency of the system.



中文翻译:

一种立体IMU系统的渐进式在线外参数标定与初始化方法

目的

本文旨在提出一种流水线来逐步处理立体惯性测量单元(IMU)系统的在线外部参数校准和估计器初始化,该流水线不需要任何先验信息,适用于各种环境下的系统初始化。

设计/方法/方法

在标定和初始化之前,采用改进的立体跟踪方法获得运动姿态,为接下来的三个步骤提供了先决条件。首先,作者将获得的位姿与 IMU 测量值对齐,并线性计算粗略的外部参数和重力矢量,为下一步优化提供初始值。其次,作者通过优化IMU的预积分,修复了视觉获得的位姿,恢复了系统的外部和惯性参数。第三,利用上一步的结果进行视觉-惯性联合优化,进一步细化外部和惯性参数。

发现

公共数据集实验和实际实验的结果表明,与现有技术相比,该方法具有更好的准确性和鲁棒性。

原创性/价值

该方法提高了外参标定和初始化的准确性,防止系统陷入局部最小值。与传统的单独求解惯导参数的方法不同,本文一次求解所有惯导参数,并将上一步的结果作为下一步优化的种子,逐步求解外部惯导参数由粗到细,避免陷入局部最小值,减少优化时的迭代次数,提高系统效率。

更新日期:2022-02-10
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