Limb Motion Tracking with Inertial Measurement Units

While the ability to perceive attitude in 3D trajectory of the movement is a basic concept of a motion capture, a 9-axis inertial measurement unit (IMU) device containing accelerometer, gyroscope and magnetometer is introduced as a challenge for motion tracking device. In this paper, a modular architecture in terms of accuracy on orientation of the sensor output, implemented for wearable motion capture system in attitude estimation. It contains 13 IMU module devices as a sensory network attached in the human body for reconstructing human attitude estimation. The system is integrated as quaternion-based implementation where several methods are separately used for achieving better result. The first proposed methods are using digital motion processor for gaining accurate data and directly calculated inside the sensor itself. Secondly, a complementary filter (CF), fused using gradient descent algorithm. Another approach method is combining CF with Mahony filter. Furthermore, all of approaches are working with DMP system to minimize the accumulative errors. As a validation, a passive manipulator robot containing encoders is used for comparison. The experimental results showed that all of the proposed methods can work properly and they represented acceptable performances and achieve accuracy for orientation.