Lightweight Generator of Synthetic IMU Sensor Data for Accurate AHRS Analysis

Hristina Radak, Christian Scheunert, Giang T. Nguyen, Vu Nguyen, F. Fitzek
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引用次数: 0

Abstract

Accurate orientation estimation is crucial in many application areas, including unmanned ground and aerial navigation for industrial automation and human motion tracking for human-robot interaction. State-of-the-art techniques leverage Inertial Measurement Units (IMU) due to their small size, low energy footprint, and ever-increasing accuracy, which provide Magnetic, Angular Rate, and Gravity (MARG) sensor measurements. Available attitude determination techniques rely on advanced signal processing algorithms to compensate for the gyroscope integration drift. The comparison of different algorithms depends solely on the collected ground-truth data set, which is difficult to replicate. This paper introduces a lightweight software framework to generate synthetic IMU sensor data. We generate the ground-truth orientation of the sensor body frame and apply an inverse navigation process to obtain corresponding synthetic sensor data. Additionally, we compare two well-known orientation estimation algorithms applied to the synthetically generated data from our framework. Evaluation results demonstrate that the proposed software framework represents a fast and easy-to-use solution to the problem of evaluation of different orientation estimation algorithms while providing access to ground truth measurements.
用于精确AHRS分析的合成IMU传感器数据轻量级生成器
准确的方向估计在许多应用领域至关重要,包括工业自动化的无人地面和空中导航以及人机交互的人体运动跟踪。最先进的技术利用惯性测量单元(IMU),因为它们体积小,能耗低,精度不断提高,可以提供磁,角速率和重力(MARG)传感器测量。现有的姿态确定技术依靠先进的信号处理算法来补偿陀螺仪的积分漂移。不同算法的比较完全依赖于收集到的真实数据集,这很难复制。本文介绍了一种生成综合IMU传感器数据的轻量级软件框架。我们生成传感器本体框架的真地方向,并应用逆导航过程获得相应的合成传感器数据。此外,我们比较了两种众所周知的方向估计算法应用于我们的框架合成生成的数据。评估结果表明,所提出的软件框架在提供对地面真值测量的访问的同时,为评估不同方向估计算法的问题提供了一种快速且易于使用的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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