Proceedings ArticleDOI
A comparison of unscented and extended Kalman filtering for estimating quaternion motion
Jr. J.J. LaViola
- Vol. 3, pp 2435-2440
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TLDR
An empirical study comparing the performance of unscented and extended Kalman filtering for improving human head and hand tracking, represented with quaternions, which are critical for correct viewing perspectives in virtual reality.Abstract:
The unscented Kalman filter is a superior alternative to the extended Kalman filter for a variety of estimation and control problems. However, its effectiveness for improving human motion tracking for virtual reality applications in the presence of noisy data has been unexplored. In this paper, we present an empirical study comparing the performance of unscented and extended Kalman filtering for improving human head and hand tracking. Specifically, we examine human head and hand orientation motion signals, represented with quaternions, which are critical for correct viewing perspectives in virtual reality. Our experimental results and analysis indicate that unscented Kalman filtering performs equivalently with extended Kalman filtering. However, the additional computational overhead of the unscented Kalman filter and quasi-linear nature of the quaternion dynamics lead to the conclusion that the extended Kalman filter is a better choice for estimating quaternion motion in virtual reality applications.read more
Citations
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Journal ArticleDOI
Quaternion-based extended Kalman filter for determining orientation by inertial and magnetic sensing
TL;DR: Improvements in the accuracy of orientation estimates are demonstrated for the proposed quaternion based extended Kalman filter, as compared with filter implementations where either the in-line calibration procedure, the adaptive mechanism for weighting the measurements of the aiding system sensors, or both are not implemented.
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Estimating Three-Dimensional Orientation of Human Body Parts by Inertial/Magnetic Sensing
TL;DR: This paper reviews the main sensor fusion and filtering techniques proposed for accurate inertial/magnetic orientation tracking of human body parts and gives useful recipes for their actual implementation.
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Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion
Alessandro Filippeschi,Norbert Schmitz,Markus Miezal,Gabriele Bleser,Gabriele Bleser,Emanuele Ruffaldi,Didier Stricker +6 more
TL;DR: Five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion and results show that all but one of the selected models perform similarly (about 35 mm average position estimation error).
Journal ArticleDOI
High-Integrity IMM-EKF-Based Road Vehicle Navigation With Low-Cost GPS/SBAS/INS
TL;DR: A set of tests performed in controlled and real scenarios proves the suitability of the proposed IMM-EKF implementation as compared with low-cost GNSS-based solutions, dead reckoning systems, single-model EKF, and other filtering approaches of the current literature.
Book
Autonomous Flying Robots: Unmanned Aerial Vehicles and Micro Aerial Vehicles
TL;DR: In this article, the authors describe step by step the development of small or miniature unmanned aerial vehicles and discuss in detail the integrated prototypes developed at the robotics laboratory of Chiba University.
References
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Journal ArticleDOI
Numerical Recipes in C: The Art of Scientific Computing
Mary C. Seiler,Fritz A. Seiler +1 more
Proceedings ArticleDOI
New extension of the Kalman filter to nonlinear systems
Simon Julier,Jeffrey Uhlmann +1 more
TL;DR: It is argued that the ease of implementation and more accurate estimation features of the new filter recommend its use over the EKF in virtually all applications.
Proceedings ArticleDOI
The unscented Kalman filter for nonlinear estimation
Eric A. Wan,R. van der Merwe +1 more
TL;DR: The unscented Kalman filter (UKF) as discussed by the authors was proposed by Julier and Uhlman (1997) for nonlinear control problems, including nonlinear system identification, training of neural networks, and dual estimation.