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- W3048488619 abstract "IMU sensor has long been developed to solve the problems with angular rotation of objects moving in space. There are variety of available IMU sensors which have built-in orientation estimation algorithms with high accuracy (AHRS) such as ADIS16480, RTxQ, XSENS. However, understanding of IMU calibration methodology and orientation estimation algorithms is still essential for further intervention or integration. This paper will focus on the orientation estimation algorithm, calibration methods and the IMU model. First, a simulation model is created to develop and evaluate the algorithm theoretically. We also build a turntable for testing, displaying, storing data from the real IMU while the orientation estimation algorithm is embedded into a microcontroller with 10-ms sampling time. Experimental results have shown that the proposed algorithm achieves accurate estimation of orientation. The angular RMS errors are all less than 2° in normal conditions as well as less disturbed in the conditions involving external acceleration and magnetic disturbance." @default.
- W3048488619 created "2020-08-18" @default.
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- W3048488619 date "2020-08-11" @default.
- W3048488619 modified "2023-09-26" @default.
- W3048488619 title "IMU Calibration Methods and Orientation Estimation Using Extended Kalman Filters" @default.
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- W3048488619 doi "https://doi.org/10.1007/978-3-030-53021-1_55" @default.
- W3048488619 hasPublicationYear "2020" @default.
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