Numerous applications require a self-contained personal navigation system that works in indoor and outdoor environments, does not require any infrastructure support, and is not susceptible to jamming. Posture tracking with an array of inertial/magnetic sensors attached to individual human limb segments has been successfully demonstrated. The "sourceless" nature of this technique makes possible full body posture tracking in an area of unlimited size with no supporting infrastructure. Such sensor modules contain three orthogonally mounted angular rate sensors, three orthogonal linear accelerometers and three orthogonal magnetometers. This paper describes a method for using accelerometer data combined with orientation estimates from the same modules to calculate position during walking and running. The periodic nature of these motions includes short periods of zero foot velocity when the foot is in contact with the ground. This pattern allows for precise drift error correction. Relative position is calculated through double integration of drift corrected accelerometer data. Preliminary experimental results for various types of motion including walking, side stepping, and running document accuracy of distance and position estimates.
%0 Conference Paper
%1 4209463
%A Yun, Xiaoping
%A Bachmann, E.R.
%A Moore, H.
%A Calusdian, J.
%B Robotics and Automation, 2007 IEEE International Conference on
%D 2007
%K algorithm imu navigation sensor tracking
%P 2526 -2533
%R 10.1109/ROBOT.2007.363845
%T Self-contained Position Tracking of Human Movement Using Small Inertial/Magnetic Sensor Modules
%U http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4209463&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4209463
%X Numerous applications require a self-contained personal navigation system that works in indoor and outdoor environments, does not require any infrastructure support, and is not susceptible to jamming. Posture tracking with an array of inertial/magnetic sensors attached to individual human limb segments has been successfully demonstrated. The "sourceless" nature of this technique makes possible full body posture tracking in an area of unlimited size with no supporting infrastructure. Such sensor modules contain three orthogonally mounted angular rate sensors, three orthogonal linear accelerometers and three orthogonal magnetometers. This paper describes a method for using accelerometer data combined with orientation estimates from the same modules to calculate position during walking and running. The periodic nature of these motions includes short periods of zero foot velocity when the foot is in contact with the ground. This pattern allows for precise drift error correction. Relative position is calculated through double integration of drift corrected accelerometer data. Preliminary experimental results for various types of motion including walking, side stepping, and running document accuracy of distance and position estimates.
@inproceedings{4209463,
abstract = {Numerous applications require a self-contained personal navigation system that works in indoor and outdoor environments, does not require any infrastructure support, and is not susceptible to jamming. Posture tracking with an array of inertial/magnetic sensors attached to individual human limb segments has been successfully demonstrated. The "sourceless" nature of this technique makes possible full body posture tracking in an area of unlimited size with no supporting infrastructure. Such sensor modules contain three orthogonally mounted angular rate sensors, three orthogonal linear accelerometers and three orthogonal magnetometers. This paper describes a method for using accelerometer data combined with orientation estimates from the same modules to calculate position during walking and running. The periodic nature of these motions includes short periods of zero foot velocity when the foot is in contact with the ground. This pattern allows for precise drift error correction. Relative position is calculated through double integration of drift corrected accelerometer data. Preliminary experimental results for various types of motion including walking, side stepping, and running document accuracy of distance and position estimates.},
added-at = {2012-09-28T20:22:07.000+0200},
author = {Yun, Xiaoping and Bachmann, E.R. and Moore, H. and Calusdian, J.},
biburl = {https://www.bibsonomy.org/bibtex/2436027140686ef3ac5878d0aa39a04c6/christian_claus},
booktitle = {Robotics and Automation, 2007 IEEE International Conference on},
doi = {10.1109/ROBOT.2007.363845},
interhash = {a2fb0e9963aa3edbe96be2affd16040a},
intrahash = {436027140686ef3ac5878d0aa39a04c6},
issn = {1050-4729},
keywords = {algorithm imu navigation sensor tracking},
month = {april},
pages = {2526 -2533},
timestamp = {2012-09-28T20:22:07.000+0200},
title = {Self-contained Position Tracking of Human Movement Using Small Inertial/Magnetic Sensor Modules},
url = {http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4209463&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D4209463},
year = 2007
}