International Journal of Aeronautical and Space Sciences

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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Motion and Structure Estimation Using Fusion of Inertial and Vision Data for Helmet Tracker

  • Heo, Se-Jong (School of Mechanical and Aerospace Engineering Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Shin, Ok-Shik (School of Mechanical and Aerospace Engineering Institute of Advanced Aerospace Technology, Seoul National University) ;
  • Park, Chan-Gook (School of Mechanical and Aerospace Engineering Institute of Advanced Aerospace Technology, Seoul National University)
  • Published : 2010.03.01
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Abstract

For weapon cueing and Head-Mounted Display (HMD), it is essential to continuously estimate the motion of the helmet. The problem of estimating and predicting the position and orientation of the helmet is approached by fusing measurements from inertial sensors and stereo vision system. The sensor fusion approach in this paper is based on nonlinear filtering, especially expended Kalman filter(EKF). To reduce the computation time and improve the performance in vision processing, we separate the structure estimation and motion estimation. The structure estimation tracks the features which are the part of helmet model structure in the scene and the motion estimation filter estimates the position and orientation of the helmet. This algorithm is tested with using synthetic and real data. And the results show that the result of sensor fusion is successful.

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References

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