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http://dx.doi.org/10.5573/ieie.2017.54.2.106

Pose Estimation Method Using Sensor Fusion based on Extended Kalman Filter  

Yun, Inyong (Department of Information and Communication Engineering, Sungkyunkwan University)
Shim, Jaeryong (LotusEco, Ltd.)
Kim, Joongkyu (LotusEco, Ltd.)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.54, no.2, 2017 , pp. 106-114 More about this Journal
Abstract
In this paper, we propose the method of designing an extended kalman filter in order to accurately measure the position of the spatial-phase system using sensor fusion. We use the quaternion as a state variable in expressing the attitude of an object. Then, the attitude of rigid body can be calculated from the accelerometer and magnetometer by applying the Gauss-Newton method. We estimate the changes of state by using the measurements obtained from the gyroscope, the quaternion, and the vision informations by ARVR_SDK. To increase the accuracy of estimation, we designed and implemented the extended kalman filter, which showed excellent ability to adjust and compensate the sensor error. As a result, we could experimentally demonstrate that the reliability of the attitude estimation value can be significantly increased.
Keywords
Extended Kalman Filter; Quaternion; Gauss-Newton Method; Pose Estimation;
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