For an anthropomorphic arm-hand robot, grasping and in-hand manipulating an object can be realized with numerous approach trajectories and grasping configurations. The redundancy at this level of the tasks is due to a large number of degrees-of-freedom (DOFs) of the arm-hand system. This redundancy constitutes a big challenge to the planning and control tasks of the robot. For this kind of tasks, human has his own choices privileging certain configurations over the others. These choices come from a long learning process which implicitly takes into account the mechanical constraints of the system. In this work, we concentrate our effort on deciphering certain mechanical constraints, "tenodesis" phenomenon in particular, in order to solve the redundancy and imitate the human natural gestures in the tasks of grasping or in-hand manipulation.