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基于模型的扩展四元数卡尔曼滤波器用于任意运动链的惯性方向跟踪。

Model-based extended quaternion Kalman filter to inertial orientation tracking of arbitrary kinematic chains.

作者信息

Szczęsna Agnieszka, Pruszowski Przemysław

机构信息

Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland.

出版信息

Springerplus. 2016 Nov 14;5(1):1965. doi: 10.1186/s40064-016-3653-8. eCollection 2016.

Abstract

Inertial orientation tracking is still an area of active research, especially in the context of out-door, real-time, human motion capture. Existing systems either propose loosely coupled tracking approaches where each segment is considered independently, taking the resulting drawbacks into account, or tightly coupled solutions that are limited to a fixed chain with few segments. Such solutions have no flexibility to change the skeleton structure, are dedicated to a specific set of joints, and have high computational complexity. This paper describes the proposal of a new model-based extended quaternion Kalman filter that allows for estimation of orientation based on outputs from the inertial measurements unit sensors. The filter considers interdependencies resulting from the construction of the kinematic chain so that the orientation estimation is more accurate. The proposed solution is a universal filter that does not predetermine the degree of freedom at the connections between segments of the model. To validation the motion of 3-segments single link pendulum captured by optical motion capture system is used. The next step in the research will be to use this method for inertial motion capture with a human skeleton model.

摘要

惯性方向跟踪仍然是一个活跃的研究领域,特别是在户外实时人体运动捕捉的背景下。现有系统要么提出松散耦合的跟踪方法,即独立考虑每个部分,并考虑由此产生的缺点,要么提出紧密耦合的解决方案,这些方案仅限于具有少数部分的固定链。这样的解决方案没有改变骨架结构的灵活性,专用于特定的关节集,并且具有高计算复杂性。本文描述了一种基于模型的新扩展四元数卡尔曼滤波器的提议,该滤波器允许基于惯性测量单元传感器的输出估计方向。该滤波器考虑了运动链结构产生的相互依赖性,从而使方向估计更加准确。所提出的解决方案是一种通用滤波器,它不预先确定模型各部分之间连接的自由度。为了验证,使用光学运动捕捉系统捕捉的三段单链摆的运动。研究的下一步将是将这种方法用于人体骨架模型的惯性运动捕捉。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/951a/5108752/2b1730c1e4ad/40064_2016_3653_Fig1_HTML.jpg

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