• DocumentCode
    296914
  • Title

    Neural networks in robotics: state of the art

  • Author

    Tzafestas, Spyros G.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Tech. Univ. of Athens, Greece
  • Volume
    1
  • fYear
    34881
  • fDate
    10-14 Jul1995
  • Firstpage
    12
  • Abstract
    This paper provides a short review of the neural network approach to system control with reference to robotic systems. Starting with an exposition of the main neurocontrol architectures, the paper overviews the literature on the application of neural networks to robot kinematics, dynamics, path planning and motion control, including some work on neurofuzzy control. To appreciate better robot neurocontrol, an unsupervised robot neurocontroller is presented in some detail. The paper includes a discussion of the criticism made to the neural control paradigms, and an outline of some interesting areas for further research
  • Keywords
    fuzzy control; fuzzy neural nets; motion control; neurocontrollers; path planning; robot dynamics; robot kinematics; unsupervised learning; application; motion control; neural network; neurocontrol architectures; neurofuzzy control; path planning; robot dynamics; robot kinematics; robotic systems; state-of-the-art; unsupervised control; Adaptive control; Automatic control; Biological neural networks; Control systems; Humans; Intelligent networks; Intelligent robots; Neural networks; Neurocontrollers; Neurons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics, 1995. ISIE '95., Proceedings of the IEEE International Symposium on
  • Conference_Location
    Athens
  • Print_ISBN
    0-7803-7369-3
  • Type

    conf

  • DOI
    10.1109/ISIE.1995.496471
  • Filename
    496471