A Cognitive Architecture for Robotic Hand Posture Learning

Haris Dindo, Antonio Chella, Irene Macaluso, Antonio Chella, Haris Dindo, Ignazio Infantino, Irene Macaluso

Risultato della ricerca: Articlepeer review

12 Citazioni (Scopus)

Abstract

This paper deals with the design and implementation of a visual control of a robotic system composed of a dexterous hand and video camera. The aim of the proposed system is to reproduce the movements of a human hand in order to learn complex manipulation tasks or to interact with the user. A novel algorithm for robust and fast fingertips localization and tracking is presented. A suitable kinematic hand model is adopted to achieve a fast and acceptable solution to an inverse kinematics problem. The system is part of a cognitive architecture for posture learning that integrates the perceptions by a high-level representation of the scene and of the observed actions. The anthropomorphic robotic hand imitates the gestures acquired by the vision system in order to learn meaningful movements, to build its knowledge by different conceptual spaces, and to perform complex interactions with the human operator.
Lingua originaleEnglish
pagine (da-a)42-52
Numero di pagine11
RivistaIEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS. PART C, APPLICATIONS AND REVIEWS
Volume35
Stato di pubblicazionePublished - 2005

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering

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