Robust pose estimation algorithm for wrist motion tracking

The wrist plays a fundamental role in reaching and grasping actions, i.e. it guides the hand to the grasp position and adjusts its orientation on the basis of the grasping type and task. This paper proposes a novel, low-cost method for wrist pose estimation by using the Asus Xtion Pro Live motion sensing device and a robust marker-based tracking approach based on Unscented Kalman Filter (UKF). The hand palm kinematic model is also considered. The applicability of the approach to evaluate some interesting kinematics parameters, such as position, orientation, Range Of Motion, angular and linear velocity and trajectory has been proved. In particular, since the nature of the paper is to present a novel approach for wrist pose estimation, only initial validation for wrist kinematic measurement will be reported.