Abstract
Current consumer electronics is equipped with various sensors, among which accelerometer, gyroscope, and magnetometer represent typical examples. In this paper, we study the possibility of using these low-cost sensors for 3D motion and orientation tracking. In particular, we thoroughly describe a simple dead-reckoning algorithm for sensor data fusion which produces a 3D path of the device in real time. More importantly, we propose a method of automated stabilization every time the device stands still, which corrects the bias caused by sensor inaccuracies. This method extends the time when motion tracking is reliable. We evaluate the proposed pipeline in a variety of experiments using two common smartphones.
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Notes
- 1.
In our case, the Android OS requires launching an application that uses the magnetometer and rotating the device in the “figure 8 pattern”.
- 2.
The technique of updating the stored values when the device is at rest is usually called zero-velocity update [18].
- 3.
We can achieve the projetion by creating a rotation matrix that rotates the gravity vector to the z axis, then rotate the \(mag_b\) and \(ori \cdot mag_c\) vectors using this matrix, set their z coordinate to zero and rotate them back.
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Acknowledgements
Research was partially supported by the Czech Science Foundation under the project P103-15-19877S and by SVV under the project 260 224.
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Matzner, F., Barták, R. (2015). Short-Term Motion Tracking Using Inexpensive Sensors. In: Pichardo Lagunas, O., Herrera Alcántara, O., Arroyo Figueroa, G. (eds) Advances in Artificial Intelligence and Its Applications. MICAI 2015. Lecture Notes in Computer Science(), vol 9414. Springer, Cham. https://doi.org/10.1007/978-3-319-27101-9_45
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