关键词: MEMS传感器, 拓展卡尔曼滤波器, 四元数, 姿态解算

Abstract: In the study of the attitude estimating optimization of the teaching arm, aiming at the low accuracy and poor stability of the traditional method that use single set of sensors for data fusion and attitude estimation, a method based on multi sets of MEMS sensors is designed. Six sets of sensors are mounted on the three axes of the carrier coordinate system, measuring two sensor data separately. The vector product of the sensor data measured by the combination and estimated by quaternion method is used as the input of the complementary filter instead of the attitude error. Fuzzy controller and PI controller adjusted the gyroscopes outputs separately according to the principle of complementary filter. Attitude is estimated through extended Kalman filter and quaternion with higher accuracy is achieved. Then it is transformed to attitude angulars. Simulation results show that, instatic and dynamic situations, the accuracy and stability of attitude data with combined adjustment based on multi sensors are improved more than that with PI adjustment based on single sensor.

Key words: MEMS sensors, extended Kalman filters, quaternion, attitude estimation