Abstract
A novel, brain-like, hierarchical (affine-neuro-fuzzy-topological) control for biomechanically realistic humanoid-robot biodynamics (HB), formulated previously in [15, 16], is proposed in the form of a tensor-invariant, “meta-cybernetic” functor machine. It represents a physiologically inspired, three-level, nonlinear feedback controller of muscular-like joint actuators. On the spinal level, nominal joint-trajectory tracking is formulated as an affine Hamiltonian control system, resembling the spinal (autogenetic-reflex) “motor servo.” On the cerebellar level, a feedback-control map is proposed in the form of self-organized, oscillatory, neurodynamical system, resembling the associative interaction of excitatory granule cells and inhibitory Purkinje cells. On the cortical level, a topological “hyper-joystick” command space is formulated with a fuzzy-logic feedback-control map defined on it, resembling the regulation of locomotor conditioned reflexes. Finally, both the cerebellar and the cortical control systems are extended to provide translational force control for moving6-degree-of-freedom chains of inverse kinematics.
Highlights
The so-called “intelligent” approach to robot control typically represents a form of function approximation, which is itself based on a combination of neuro-fuzzy-genetic computations
We consider the muscle-like covariant driving torques, that is, one-forms Fi = Fi(t, q, p), which are dependent on time t, joint angles q = q(t), and canonical angular momenta p = p(t), as the most important component of humanoid motion; we propose the sophisticated hierarchical system for the subtle Fi-control corresponding to the spinal, the cerebellar, and the cortical levels of human motor control
This paper proposes the new, brain-like, hierarchical control for the previously developed biomechanically realistic humanoid robot dynamics
Summary
Traditional hierarchical robot control (see, e.g., [31]) consists of three control levels: the executive (bottom) level performs tracking of nominal trajectories in internal joint coordinates, the strategic (top) level performs “planning” of the trajectories of an end-effector in external Cartesian coordinates, and the tactical (middle) level connects other two levels by means of inverse kinematics. We consider the muscle-like covariant driving torques, that is, one-forms Fi = Fi(t, q, p), which are dependent on time t, joint angles q = q(t), and canonical angular momenta p = p(t), as the most important component of humanoid motion (this is based on the fact of extremely high degree of the natural muscular redundancy: the human body, which is an everlasting inspiration for humanoid robots, for its motion uses a synergetic action of approximately 640 skeletal muscles); we propose the sophisticated hierarchical system for the subtle Fi-control corresponding to the spinal, the cerebellar, and the cortical levels of human motor control. The model of the cortical FC level, presented in this paper, mimics the integral synergistic regulation of (loco)motor conditioned reflexes [10] Both cerebellar control systems can be extended to provide translational force control for moving 6-degree-of-freedom inverse kinematics chains. Computer-algebra implementation of all three FC levels of HB is provided in the appendix
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