• DocumentCode
    2741763
  • Title

    A Learning Rule-Based Robotics Hand Optimal Force Closure

  • Author

    Al-Gallaf, E. Mattar

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Univ. of Bahrain, Bahrain, Bahrain
  • fYear
    2010
  • fDate
    28-30 July 2010
  • Firstpage
    60
  • Lastpage
    66
  • Abstract
    This article presents an intelligent fuzzy rule-based approach for computing optimal set of joints torques, for manipulating a grasped object by a dexterous multi-fingered robotics hand. The intelligent approached followed here, is to let a learning fuzzy system to approximate a nonlinear force formulation for optimal contact forces. This has been achieved via following two major steps: The first was to formulate the optimal fingertips force distribution as a quadratic force optimization problem, hence to generate a large set of data. The second step was to involve a learning fuzzy system (Neuro- Fuzzy System) to learn the nonlinear relations governing fingertips forces (ℝ∈12 × 1) to hand joint torques (ℝ∈12 × 1). Simulation results show that the proposed Neuro-Fuzzy network do achieve optimal grasping force in real time.
  • Keywords
    dexterous manipulators; force control; fuzzy neural nets; fuzzy systems; learning (artificial intelligence); manipulator dynamics; torque; dexterous multi fingered robotics hand; intelligent fuzzy rule; joints torques; learning fuzzy system; learning rule; neuro fuzzy network; nonlinear force formulation; robotics hand optimal force closure; Fingers; Force; Friction; Grasping; Joints; Optimization; Robots; Dexterous Hands; Keywords- Grasping; Learning Neuro-fuzzy.;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence, Communication Systems and Networks (CICSyN), 2010 Second International Conference on
  • Conference_Location
    Liverpool
  • Print_ISBN
    978-1-4244-7837-8
  • Electronic_ISBN
    978-0-7695-4158-7
  • Type

    conf

  • DOI
    10.1109/CICSyN.2010.57
  • Filename
    5614691