Abstract
In robot inertial navigation systems, to deal with the problems of drift and noise in the gyroscope and accelerometer and the high computational cost when using extended Kalman filter (EKF) and particle filter (PF), a complementary filtering algorithm is utilized. By combining the Inertial Measurement Unit (IMU) multi-sensor signals, the attitude data are corrected, and the high-precision attitude angles are obtained. In this paper, the quaternion algorithm is used to describe the attitude motion, and the process of attitude estimation is analyzed in detail. Moreover, the models of the sensor and system are given. Ultimately, the attitude angles are estimated by using the quaternion extended Kalman filter, linear complementary filter, and Mahony complementary filter, respectively. The experimental results show that the Mahony complementary filtering algorithm has less computational cost than the extended Kalman filtering algorithm, while the attitude estimation accuracy of these two algorithms is similar, which reveals that Mahony complementary filtering is more suitable for low-cost embedded systems.
Highlights
Definition of Coordinates and Attitude DescriptionA coordinate system needs to be established before attitude description
The results show that the Mahony complementary filtering algorithm has less computational cost than the quaternion extended Kalman filtering algorithm when the attitude estimation accuracy of these two algorithms is similar, which indicates that Mahony can be better applied to low-cost embedded systems
Based on the STM32F107 hardware platform, integrating the data from the gyroscope directly to get the attitude of the robot will result in big errors and even the estimated angles will diverge owing to the low-frequency noise
Summary
A coordinate system needs to be established before attitude description. The RightA coordinate system needs to be established before attitude description. Front-Up coordinate system is selected as the carrier coordinate system The carrier coordinate system is fixedly connected with thepositive body, and the coordinate axis. Yaw angle in the Right-Front-Up coordinate system, respectively. PositiveAs directions x-axis, OXYZ is system is selected as the navigation is shownofinthe. 2, y-axis, and z-axis as East, North, and Sky. the carrier coordinate system, and we define the positive directions of the x-axis, y-axis, and z-axis as East, North, and Sky
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