The hypothesis that the central nervous system (CNS) generates movement as a shift of the limb's equilibrium posture has been corroborated experimentally in studies involving single- and multijoint motions. Posture may be controlled through the choice of muscle length-tension curve that set agonist-antagonist torque-angle curves determining an equilibrium position for the limb and the stiffness about the joints. Arm trajectories seem to be generated through a control signal defining a series of equilibrium postures. The equilibrium-point hypothesis drastically simplifies the requisite computations for multijoint movements and mechanical interactions with complex dynamic objects in the environment. Because the neuromuscular system is springlike, the instantaneous difference between the arm's actual position and the equilibrium position specified by the neural activity can generate the requisite torques, avoiding the complex “inverse dynamic” problem of computing the torques at the joints. The hypothesis provides a simple, unified description of posture and movement as well as contact control task performance, in which the limb must exert force stably and do work on objects in the environment. The latter is a surprisingly difficult problem, as robotic experience has shown. The prior evidence for the hypothesis came mainly from psychophysical and behavioral experiments. Our recent work has shown that microstimulation of the frog spinal cord's premotoneural network produces leg movements to various positions in the frog's motor space. The hypothesis can now be investigated in the neurophysiological machinery of the spinal cord.

Control laws are described for solving the task of stabilization of motion and force of interaction of a robot with its environment with a prescribed quality of transient processes with respect to position and in the presence of control, motion, and interaction force constraints. The robustness of these laws to parametric perturbations and their stability with respect to initial and external perturbations and measuring sensor errors have been proven.

In robotic tasks where the manipulator has to make transition from free space motion to constrained one, there always exists a inevitable impact phase (contact transition phase). Examples can be the autonomous exploratory motion of the end-effector in a cluttered environment, or grasping and manipulation of objects using dexterous mechanical end-effector. A number of controllers have been proposed in the literature with various discussions on their practical implications. In this paper a simple and efficient controller is proposed for the robotic contact tasks. The controller is based on the notion of switching control law where the structure of the controller remains unchanged during the phase transition and only the magnitudes of its gains are changed. The proposed control law maintans the stable performance during the impact phase of the manipulator when making contact with general environment. In addition, the controller exhibits stable and robust performance during the post-contact phase with the desired contact force regulation. The stability of the proposed controller is shown using the Lyapunov method which guarantees the exponential rate of convergence of the state during the contact transition to post-contact phase. Experimental results are presented to demonstrate the practicality of the proposed controller.

An adaptive control of multiple robot compliant manipulation of a dynamical environment is synthesized. It may be implemented when: (i) there is no good understanding of all physical effects incorporated in the multiple robots/object/environment system to be controlled; (ii) the parameters of the system are not precisely known, (iii) the system parameters do vary in a known region about their nominal values. The proposed adaptive control law has the inverse dynamics controller structure and is composed of an identification part (parameter update law), and a control law part. It is proved that the proposed adaptive controller is asymptotically stable. The simulation results verify the proposed approach to coordinated adaptive control of multiple robot manipulators in constrained motion tasks. They also verify that the multiple robots/object/environment system can track a step parameter change.