• DocumentCode
    1604174
  • Title

    Remote Robot Training of Its Artificial Neural Network through GSM Communication

  • Author

    Ramu, G. Venkat ; Hariprakash, R. ; Visalakshi, K. ; Ananthi, S. ; Padmanabhan, K.

  • Author_Institution
    Univ. of Madras, Chennai
  • fYear
    2008
  • Firstpage
    355
  • Lastpage
    358
  • Abstract
    Without building new technology and involved hardware circuit boards, how to develop industrial artificial neural network (ANN) based robotic projects for enterprises is explained with special reference to GSM cell and robotic models. In the process of training to develop enterprise robots, one has to make use of all possible resources. Without the need for development of new circuits or methodology, existing devices, components and services can be used to develop a standard robotic project. There are many examples like traffic control, agricultural plantation and adaptive surveillance. The groundwork of technology for the above robot data collection and control is elucidated and schemes using simple readily available hardware for easy and quick rigging up of robotic systems is the theme of this paper.
  • Keywords
    control engineering computing; neural nets; telerobotics; GSM communication; artificial neural network; hardware circuit boards; remote robot training; robot data collection; Adaptive control; Artificial neural networks; GSM; Industrial training; Neural network hardware; Printed circuits; Programmable control; Service robots; Standards development; Traffic control; Artificial Neural Network.GSM; GPRS network; Remote robot training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems and Networks Communications, 2008. ICSNC '08. 3rd International Conference on
  • Conference_Location
    Sliema
  • Print_ISBN
    978-0-7695-3371-1
  • Type

    conf

  • DOI
    10.1109/ICSNC.2008.39
  • Filename
    4693696