Posture Estimation for a High Degree of Freedom Anthropomorphic Tendon-Based Hand Model – A Simulation Experiment

Tendon-based anthropomorphic robotic hand implementations generally lack the ability to measure the joint angles, as the encoder installed for directly measuring the joint angle may compromise the dexterity of the hand. In this paper, we present a computational approach to estimate the joint positions of the hand using the measured tendon displacements and tensions. First, we introduce an efficient framework for the kinematic description of an anthropomorphic hand based on Denavit-Hartenberg's description. Then, we use a simplified tendon model to derive a system of nonlinear equations for the joint positions, which is finally solved by a gradient-based optimization solver. We used the model to control the hand along commanded gestures by feeding back the estimated joint angles through the moment arm Jacobian. The effectiveness and limitations of this method is illustrated in MuJoCo simulation environment on the Anatomically Correct Biomechatronic Hand having a 5 and 6 degrees of freedom kinematic models for the long fingers and the thumb, respectively.