Augmented reality (AR) systems are often used to superimpose
virtual objects or information on a scene to improve situational
awareness. Delays in the display system or inaccurate registration
of objects destroy the sense of immersion a user experiences when
using AR systems. AC electromagnetic trackers are ideal for these
applications when combined with head orientation prediction to
compensate for display system delays. Unfortunately, these trackers
do not perform well in environments that contain conductive or
ferrous materials due to magnetic field distortion without
expensive calibration techniques. In our work we focus on both the
prediction and distortion compensation aspects of this application,
developing a "small footprint" predictive filter for display lag
compensation and a simplified calibration system for AC magnetic
trackers. In the first phase of our study we presented a novel
method of tracking angular head velocity from quaternion
orientation using an Extended Kalman Filter in both single model
(DQEKF) and multiple model (MMDQ) implementations. In the second
phase of our work we have developed a new method of mapping the
magnetic field generated by the tracker without high precision
measurement equipment. This method uses simple fixtures with
multiple sensors in a rigid geometry to collect magnetic field data
in the tracking volume. We have developed a new algorithm to
process the collected data and generate a map of the magnetic field
distortion that can be used to compensate distorted measurement
data. Table of Contents: List of Tables / Preface / Acknowledgments
/ Delta Quaternion Extended Kalman Filter / Multiple Model Delta
Quaternion Filter / Interpolation Volume Calibration / Conclusion /
References / Authors' Biographies
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