Neville Hogan

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  How do we manage it? The paradox of human performance
  Neville Hogan

  Despite vastly slower ‘hardware’ (e.g. muscles) and ‘wetware’ (e.g. neurons) human dexterity and agility significantly out-perform contemporary robots. How is this possible? Slow actuators and long communication delays require predictive control based on some form of internal model—but what form? One possible answer is based on dynamic primitives; they enable highly dynamic behavior with minimal high-level supervision and intervention. Supporting this proposal, I will review a surprising limitation arising from control via dynamic primitives—moving slowly is hard for humans. Controlling physical interaction requires a special class of dynamic primitives, mechanical impedances. Both motion and interaction primitives may be combined by a nonlinear generalization of the classical equivalent electrical circuit. It reconciles contrasting constraints of information-processing (computation) and energy-processing (physical dynamics). I suggest that nonlinear equivalent networks provide a general basis for the internal models required for high-performance interactive control, and especially physical human-robot interaction.