Abstract
This paper discusses the development of the attitude estimation algorithm for a MEMS based 9-axis motion tracking sensor, which includes a tri-axis accelerometer, a tri-axis gyroscope and a tri-axis magnetometer. The comparison between the Euler angles and the direction cosine matrix (DCM) based approach is presented to illustrate the advantage of DCM. It will be shown that the kinematic model for DCM can be transformed into a linear time-varying state space form, which greatly simplifies the development of the estimation algorithm. Different from the existing estimation algorithms, which incorporate a nonlinear kinematic model and the nonlinear Kalman filter, such as extended Kalman filter (EKF) or unscented Kalman filter (UKF), the nonlinearity in the kinematic model is not the trouble maker anymore. Hence, global convergence can always be guaranteed. Finally, the estimation algorithm is demonstrated by using the real measurement data collected from InvenSenses MPU9250, which is one of the most popular 9-axis motion tracking sensors in the market.
Original language | English (US) |
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Title of host publication | Mechatronics; Mechatronics and Controls in Advanced Manufacturing; Modeling and Control of Automotive Systems and Combustion Engines; Modeling and Validation; Motion and Vibration Control Applications; Multi-Agent and Networked Systems; Path Planning and Motion Control; Robot Manipulators; Sensors and Actuators; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamic Controls; Vehicle Dynamics and Traffic Control |
Publisher | American Society of Mechanical Engineers |
ISBN (Electronic) | 9780791850701 |
DOIs | |
State | Published - 2016 |
Event | ASME 2016 Dynamic Systems and Control Conference, DSCC 2016 - Minneapolis, United States Duration: Oct 12 2016 → Oct 14 2016 |
Publication series
Name | ASME 2016 Dynamic Systems and Control Conference, DSCC 2016 |
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Volume | 2 |
Other
Other | ASME 2016 Dynamic Systems and Control Conference, DSCC 2016 |
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Country/Territory | United States |
City | Minneapolis |
Period | 10/12/16 → 10/14/16 |
Bibliographical note
Publisher Copyright:Copyright © 2016 by ASME.