Rigid body motions capturing by means of wearable inertial and magnetic MEMS sensors assembly: toward the reconstitution of the posture of free ranging animal in Bio-logging

In this chapter, we focused on the posture estimation problem of a body moving in 3D space. This study is devoted to the reconstruction of the body attitude and Dynamic Body Acceleration (DBA) in free ranging animal (application in Bio-logging) where the access to GPS locations is limited or impossible. A quaternion-based complementary filter is designed to provide a viable attitude estimation method. We claim that this approach is an alternative to overcome the limitations of the Extended Kalman Filter (EKF). The complementary filter processes data from small inertial/magnetic sensor modules that contains triaxial gyroscopes, accelerometers, and magnetometers without resorting to GPS data. The proposed algorithm incorporates a motion kinematic model and adopts a two-layer filter architecture. In the latter, the Levenberg Marquardt Algorithm (LMA) pre-processes acceleration and local magnetic field measurements to produce what will be called the modelling error. This error together with the angular rate measurements becomes measurement signals for the complementary filter. By this way, the overall approach design is greatly simplified. The efficiency of the approach is experimentally investigated through a free motion of animal. The complementary filter performance is shown also quantitatively using the Root Mean Square Difference (RMSD). The estimated attitude is used after to calculate the DBA for future evaluation of the energetic index of animal and its 3D position.