A minimum-order Kalman filter for ambulatory real-time human body orientation tracking

Authors:
Jung Keun Lee;Edward J. Park
Affiliations:
School of Engineering Science, Simon Fraser University, Surrey, BC, Canada;School of Engineering Science, Simon Fraser University, Surrey, BC, Canada
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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An Introduction to the Kalman Filter

An Introduction to the Kalman Filter
Design, Implementation, and Experimental Results of a Quaternion-Based Kalman Filter for Human Body Motion Tracking

IEEE Transactions on Robotics

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Abstract

In this paper, a computationally efficient orientation estimation algorithm using an inertial/magnetic sensor is presented for ambulatory real-time human motion tracking. Based on a quaternion formulation, the proposed algorithm is designed to have two main steps that are connected in feedback relationship: a quaternion measurement step with a vector selector scheme and a Kalman filter (KF) step. This allows us to choose only the quaternion as the state and measurement vectors in our KF design. Thus, the KF has a minimum-order structure (i.e., 4th-order), which decreases the computational cost. The estimated orientation accuracy is validated experimentally by using an optical tracking system.