This paper aims at challenging Bernstein's problem called the "Degrees-of-Freedom problem," which remains unsolved from both the physiological and robotics viewpoints. More than a half century ago A.N. Bernstein observed that "dexterity" residing in human limb motion emerges from accumulated involvement of multi-joint movements in surplus DOF. It is also said in robotics that redundancy of DOFs in robot mechanisms may contribute to enhancement of dexterity and versatility. However, kinematic redundancy incurs a problem of ill-posedness of inverse kinematics from task-description space to joint space. In the history of robotics research such ill-posedness problem of inverse-kinematics has not yet been attacked directly but circumvented by introducing an artificial performance index and determining uniquely an inverse kinematics solution by minimizing it. Instead of it, this paper introduces two novel concepts named "stability on a manifold" and "transferability to a submanifold" in treating the case of human multi-joint movements of reaching and shows that a sensory feedback from task space to joint space together with a set of adequate dampings enables any solution to the overall closed-loop dynamics to converge naturally and coordinately to a lower-dimensional manifold describing a set of joint states fulfilling a given motion task. This means that, without considering any type of inverse kinematics, the reaching task can be accomplished by a sensory feedback with adequate choice of a stiffness parameter and damping coefficients. It is also shown that these novel concepts can cope with annoying characteristics called "variability" of redundant joint motions seen typically in human skilled reaching. Finally, it is pointed out that the proposed control signals can be generated in a feedforward manner in case of human limb movements by referring to mechano-chemical characteristics of activation of muscles. Based on this observation, generation of human skilled movements of reaching can be interpreted in terms of the proposed "Virtual-Spring" hypothesis instead of the traditional "Equilibrium-Point" hypothesis.

This paper addresses the important issue of estimating realistic grasping postures, and presents a methodology and algorithm to automate the generation of hand and body postures during the grasp of arbitrary shaped objects. Predefined body postures stored in a database are generalized to adapt to a specific grasp using inverse kinematics. The reachable space is represented discretely dividing into small subvolumes, which enables to construct the database. The paper also addresses some common problems of articulated figure animation. A new approach for body positioning with kinematic constraints on both hands is described. An efficient and accurate manipulation of joint constraints is presented. Obtained results are quite satisfactory, and some of them are shown in the paper. The proposed algorithms can find application in the motion of virtual actors, all kinds of animation systems including human motion, robotics and some other fields such as medicine, for instance, to move the artificial limbs of handicapped people in a natural way.