Abstract
A five-axis camera stabilizer based on quaternion unscented Kalman filter algorithm is designed. It combined the unscented Kalman filter algorithm with the quaternion attitude solution and was solved by attitude sensor. By attitude algorithm, the motor in three directions of pitch, heading and roll in the stabilizer was accurately adjusted to control the movement of the three electronic arms. In order to improve the three-axis hand-held camera stabilizer’s performance, and to solve the jitter problem of up-and-down movement not being eliminated, two mechanical anti-shake arms were loaded under the stabilizer to balance the camera’s picture in pitch, roll, heading, and above and below five directions. Movement can maintain a stable effect. The simulation results show that the algorithm can effectively suppress the attitude angle divergence and improve the attitude calculation accuracy.
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Acknowledgements
The research of this thesis is supported by the Guangxi Key R&D projects of Guangxi Science and Technology Program (AB17195042) and the Guangxi Innovation Drive Development Special Fund Project (AA1811009). We sincerely thank you. Special thanks to Shenzhen Wit Intelligent Co., Ltd. for their assistance in this design.
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Cheng, X., Zhang, Y., Liu, D. (2019). Design of Five-Axis Camera Stabilizer Based on Quaternion Untracked Kalman Filtering Algorithm. In: Mao, R., Wang, H., Xie, X., Lu, Z. (eds) Data Science. ICPCSEE 2019. Communications in Computer and Information Science, vol 1059. Springer, Singapore. https://doi.org/10.1007/978-981-15-0121-0_16
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DOI: https://doi.org/10.1007/978-981-15-0121-0_16
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