Two-wheel self-balancing robot attitude calculation method based on improved Extended Kalman Filter algorithm

The present invention relates to a two-wheel self-balancing robot attitude calculation method based on the improved Extended Kalman Filter algorithm. In the prior art, the existing two-wheel self-balancing robot attitude calculation method can not well meet accuracy, real-time property, simplicity and other requirements. Baed on the problems of the existing two-wheel self-balancing robot attitude calculation method, the method of the present invention utilizes the improved Extended Kalman Filter algorithm so as to effectively combine the inertial sensor attitude measurement data, compensate the gyroscope random drift error and reduce the influence of the displacement acceleration of the two-wheel self-balancing robot on the attitude calculation during moving. The two-wheel self-balancing robot attitude calculation method of the present invention can further be simultaneously applied for the two-wheel self-balancing electric vehicle. The results of static experiments, simulated platform experiments and practical dynamic experiments of the two-wheel self-balancing robot verify that the attitude calculation accuracy of the two-wheel self-balancing robot can be increased with the method of the present invention.