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Passive Motion Paradigm: An Alternative to Optimal Control
by
Morasso, Pietro
, Mohan, Vishwanathan
in
Cognitive ability
/ Cognitive architectures
/ Computational neuroscience
/ Control theory
/ Covert Actions
/ Cybernetics
/ iCub Humanoid
/ Mental task performance
/ motor control
/ Motor task performance
/ Nervous system
/ Neurorobotics
/ Neurosciences
/ Observational learning
/ optimal control theory
/ Passive Motion Paradigm
/ Robotics
/ Simulation
2011
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Passive Motion Paradigm: An Alternative to Optimal Control
by
Morasso, Pietro
, Mohan, Vishwanathan
in
Cognitive ability
/ Cognitive architectures
/ Computational neuroscience
/ Control theory
/ Covert Actions
/ Cybernetics
/ iCub Humanoid
/ Mental task performance
/ motor control
/ Motor task performance
/ Nervous system
/ Neurorobotics
/ Neurosciences
/ Observational learning
/ optimal control theory
/ Passive Motion Paradigm
/ Robotics
/ Simulation
2011
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Do you wish to request the book?
Passive Motion Paradigm: An Alternative to Optimal Control
by
Morasso, Pietro
, Mohan, Vishwanathan
in
Cognitive ability
/ Cognitive architectures
/ Computational neuroscience
/ Control theory
/ Covert Actions
/ Cybernetics
/ iCub Humanoid
/ Mental task performance
/ motor control
/ Motor task performance
/ Nervous system
/ Neurorobotics
/ Neurosciences
/ Observational learning
/ optimal control theory
/ Passive Motion Paradigm
/ Robotics
/ Simulation
2011
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Passive Motion Paradigm: An Alternative to Optimal Control
Journal Article
Passive Motion Paradigm: An Alternative to Optimal Control
2011
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Overview
IN THE LAST YEARS, OPTIMAL CONTROL THEORY (OCT) HAS EMERGED AS THE LEADING APPROACH FOR INVESTIGATING NEURAL CONTROL OF MOVEMENT AND MOTOR COGNITION FOR TWO COMPLEMENTARY RESEARCH LINES: behavioral neuroscience and humanoid robotics. In both cases, there are general problems that need to be addressed, such as the \"degrees of freedom (DoFs) problem,\" the common core of production, observation, reasoning, and learning of \"actions.\" OCT, directly derived from engineering design techniques of control systems quantifies task goals as \"cost functions\" and uses the sophisticated formal tools of optimal control to obtain desired behavior (and predictions). We propose an alternative \"softer\" approach passive motion paradigm (PMP) that we believe is closer to the biomechanics and cybernetics of action. The basic idea is that actions (overt as well as covert) are the consequences of an internal simulation process that \"animates\" the body schema with the attractor dynamics of force fields induced by the goal and task-specific constraints. This internal simulation offers the brain a way to dynamically link motor redundancy with task-oriented constraints \"at runtime,\" hence solving the \"DoFs problem\" without explicit kinematic inversion and cost function computation. We argue that the function of such computational machinery is not only restricted to shaping motor output during action execution but also to provide the self with information on the feasibility, consequence, understanding and meaning of \"potential actions.\" In this sense, taking into account recent developments in neuroscience (motor imagery, simulation theory of covert actions, mirror neuron system) and in embodied robotics, PMP offers a novel framework for understanding motor cognition that goes beyond the engineering control paradigm provided by OCT. Therefore, the paper is at the same time a review of the PMP rationale, as a computational theory, and a perspective presentation of how to develop it for designing better cognitive architectures.
Publisher
Frontiers Research Foundation,Frontiers Media S.A
Subject
/ Robotics
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