Abstract
In the inertial motion capture system, the model complexity and the large amount of computation make the completion of the orientation estimation algorithm rely solely on PC. Because the data processing speed is slow, it is difficult to realize high-speed motion tracking in the embedded system. In order to further expand the application of the motion tracking technology, this paper introduces a two-step Kalman filter, which is suitable for the embedded system. The filter is composed of two sub filters, and is adaptively adjusted based on the variance matching of fuzzy logic. IMU orientation is calculated based on the filtered acceleration vector and the estimated yaw. This approach simplifies the mathematical model, reduces the matrix operations and improves the speed of computation.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
