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Sensorimotor Self-organization via Circular-Reactions.

Dongcheng He1, Haluk Ogmen1

  • 1Laboratory of Perceptual and Cognitive Dynamics, Department of Electrical & Computer Engineering, Ritchie School of Engineering and Computer Science, University of Denver, Denver, CO, United States.

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|December 30, 2021
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Summary
This summary is machine-generated.

Newborns use circular reactions for coordinated movements. This study models goal-directed reaching using these innate abilities and self-generated exploration for accurate motor control.

Keywords:
cognitive modelingdevelopmental roboticsperception-action couplingreachingsensorimotor learning

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Area of Science:

  • Developmental robotics
  • Computational neuroscience
  • Artificial intelligence

Background:

  • Newborns exhibit innate sensory-motor coordination via reflexes and circular reactions.
  • Circular reactions involve self-generated actions leading to sensory-motor correlations.
  • Understanding these innate mechanisms can inform artificial systems.

Purpose of the Study:

  • To model goal-directed reaching in newborns based on circular reactions.
  • To investigate the role of exocentric reference frames in sensory-motor control.
  • To develop a computational model using physiologically plausible components.

Main Methods:

  • Constructed a model integrating visual processing modules and arm-control neural networks.
  • Incorporated ego- and exocentric reference frames for sensory input mapping.
  • Utilized vector representations for motor systems and local associative learning.
  • Simulated the model in a 3D environment using Unity3D.

Main Results:

  • The model successfully self-organized to generate accurate arm movements.
  • Self-generated activities were key to achieving goal-directed reaching.
  • The model demonstrated tolerance to various sources of noise in movements.

Conclusions:

  • Circular reactions and self-generated exploration are fundamental for developing goal-directed reaching.
  • The proposed model provides a biologically plausible framework for understanding infant motor development.
  • This approach can advance research in developmental robotics and artificial motor control.