方向(向量空间)
计算机科学
四元数
惯性测量装置
卡尔曼滤波器
惯性参考系
陀螺仪
惯性导航系统
偏移量(计算机科学)
人工智能
计算机视觉
数学
工程类
物理
几何学
量子力学
程序设计语言
航空航天工程
作者
Daniel Laidig,Ive Weygers,Simon Bachhuber,Thomas Seel
标识
DOI:10.23919/fusion49751.2022.9841356
摘要
We present a versatile quaternion-based inertial orientation estimation filter (VQF). Inclination drift from gyroscope strapdown integration is corrected from specific force measurements that are low-pass filtered in an almost-inertial frame to effectively compensate for instantaneous accelerations and decelerations. Heading drift is corrected via a scalar heading offset. The resulting decoupled state representation enables simultaneous 6D and 9D orientation estimation. We systematically evaluated the method on a rich orientation estimation benchmark dataset and show that the proposed method clearly outperforms three of the currently most commonly adopted and accurate inertial orientation estimation filters. The filter is available as open-source software, and its parameters are tuned to work well for a wide range of movements and application scenarios. The fundamentally different filtering approach with a decoupled state representation and novel inclination correction resulted in an unprecedented level of accuracy, with 41% lower orientation estimation errors and a twice-as-high inclination accuracy compared to existing state-of-the-art methods. This facilitates new and exciting high-precision applications in the field of inertial motion tracking.
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