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

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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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Author notes

  1. Giancarlo Teti

    Present address: RoboTech srl, Peccioli (Pisa), Italy

Authors and Affiliations

  1. ARTS (Advanced Robotics Technology and Systems) Lab, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà, 33, 56127, Pisa, Italy

    Cecilia Laschi, Gioel Asuni, Giancarlo Teti, Maria Chiara Carrozza & Paolo Dario

  2. CIR—Center for Integrated Research, Laboratory of Biomedical Robotics and Biomicrosystems, Campus-Biomedico University, Rome, Italy

    Eugenio Guglielmelli

  3. Umeå University, Umeå, Sweden

    Roland Johansson

  4. Toyota Motor Europe, Brussels, Belgium

    Hitoshi Konosu & Zbigniew Wasik

Authors
  1. Cecilia Laschi
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  2. Gioel Asuni
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  3. Eugenio Guglielmelli
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  4. Giancarlo Teti
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  5. Roland Johansson
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  6. Hitoshi Konosu
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  7. Zbigniew Wasik
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  8. Maria Chiara Carrozza
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  9. Paolo Dario
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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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  • DOI: https://doi.org/10.1007/s10514-007-9065-4

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