EAN: 9783031003943

SYNTHESIS LECTURES ON ALGORITHMS AND SOFTWARE I...

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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