Abstract
Orientation estimation from magnetic, angular rate, and gravity (MARG) sensor array is a key problem in mechatronic-related applications. This paper proposes a new method in which a quaternion-based Kalman filter scheme is designed. The quaternion kinematic equation is employed as the process model. With our previous contributions, we establish the measurement model of attitude quaternion from accelerometer and magnetometer, which is later proved to be the fastest (computationally) one among representative attitude determination algorithms of such sensor combination. Variance analysis is later given enabling the optimal updating of the proposed filter. The algorithm is implemented on real-world hardware where experiments are carried out to reveal the advantages of the proposed method with respect to conventional ones. The proposed approach is also validated on an unmanned aerial vehicle during a real flight. Results show that the proposed one is faster than any other Kalman-based ones and even faster than some complementary ones while the attitude estimation accuracy is maintained.
Highlights
In many robotic applications, the system needs to obtain the orientation parameters of some vital mechanical parts so that it can precisely control the actuators [1]
Using the attitude determination algorithm proposed in the last section as the observation model, we model the system by qmeasure,푡 = qacc,mag,푡, where
According to the official datasheet of the AHRS, the inside attitude estimation program is formed by EKF providing users with highly reliable attitude estimation
Summary
The system needs to obtain the orientation parameters of some vital mechanical parts so that it can precisely control the actuators [1]. The orientation parameters consist of the roll, pitch, and yaw angles, namely, the frequently used Euler angles [2]. MARG sensors, that is, the gyroscope, accelerometer, and magnetometer, are employed to compute the orientation [3, 4]. Modern technological advances have allowed for the massive production of microelectromechanical-system (MEMS) inertial sensors, which are highly compactly integrated [5]. There are many other sensor combinations, for example, the gyro-accelerometer and gyro-magnetometer ones, which have been discussed in [6]. There has been many efforts around the sensor fusion techniques of MARG sensors
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