Presentation

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

Manuscript

Summary

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.