A bio-inspired predictive sensory-motor coordination scheme for robot reaching and preshaping

Abstract

This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image.

The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.

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Correspondence to Cecilia Laschi.

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Laschi, C., Asuni, G., Guglielmelli, E. et al. A bio-inspired predictive sensory-motor coordination scheme for robot reaching and preshaping. Auton Robot 25, 85–101 (2008). https://doi.org/10.1007/s10514-007-9065-4

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Keywords

  • Predictive control
  • Sensory-motor coordination
  • Robot grasping
  • Robot learning
  • Expected perception
  • Internal models
  • Neuro-fuzzy controllers