Kinematic Calibration Under the Expectation Maximization Framework for Exoskeletal Inertial Motion Capture System

IF 1.9 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Journal of Systems Engineering and Electronics Pub Date : 2024-07-04 DOI:10.23919/jsee.2024.000050
Weiwei Qin, Wenxin Guo, Chen Hu, Gang Liu, Tainian Song
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Abstract

This study presents a kinematic calibration method for exoskeletal inertial motion capture (EI-MoCap) system with considering the random colored noise such as gyroscopic drift. In this method, the geometric parameters are calibrated by the traditional calibration method at first. Then, in order to calibrate the parameters affected by the random colored noise, the expectation maximization (EM) algorithm is introduced. Through the use of geometric parameters calibrated by the traditional calibration method, the iterations under the EM framework are decreased and the efficiency of the proposed method on embedded system is improved. The performance of the proposed kinematic calibration method is compared to the traditional calibration method. Furthermore, the feasibility of the proposed method is verified on the EI-MoCap system. The simulation and experiment demonstrate that the motion capture precision is significantly improved by 16.79% and 7.16% respectively in comparison to the traditional calibration method.
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外骨骼惯性运动捕捉系统期望最大化框架下的运动学校准
本研究提出了一种考虑到陀螺仪漂移等随机彩色噪声的外骨骼惯性运动捕捉(EI-MoCap)系统运动学校准方法。在该方法中,首先使用传统校准方法校准几何参数。然后,为了校准受随机彩色噪声影响的参数,引入了期望最大化(EM)算法。通过使用传统校准方法校准的几何参数,减少了 EM 框架下的迭代次数,提高了拟议方法在嵌入式系统上的效率。将所提出的运动学校准方法的性能与传统校准方法进行了比较。此外,还在 EI-MoCap 系统上验证了所提方法的可行性。模拟和实验结果表明,与传统校准方法相比,运动捕捉精度分别提高了 16.79% 和 7.16%。
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来源期刊
Journal of Systems Engineering and Electronics
Journal of Systems Engineering and Electronics 工程技术-工程:电子与电气
CiteScore
4.10
自引率
14.30%
发文量
131
审稿时长
7.5 months
期刊介绍: Information not localized
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