Human Motion Tracking based on Complementary Kalman Filter

Zhibo Wang • Lin Yang • Zhipei Huang • Jiangkang Wu • Zhiqiang Zhang • Lixin Sun

10:45 - 11:30 | Wednesday 10 May 2017 | Einstein Auditorium Foyer



Miniaturized Inertial and Magnetic Sensor Unit (IMU) has been widely used in many motion capturing applications. In order to overcome stability and noise problems of IMU, a lot of efforts have been made to develop appropriate data fusion method to obtain reliable orientation estimation from IMU data. This article presents a method which models the errors of orientation, gyroscope bias and magnetic disturbance, and compensate the errors of state variables with complementary Kalman filter in a body motion capture system. Experimental results have shown that the proposed method significantly reduces the accumulative orientation estimation errors.