• DocumentCode
    599619
  • Title

    Intelligent autonomous vehicle navigated by using artificial neural network

  • Author

    Mahmud, F. ; Arafat, Ahmad ; Zuhori, Syed Tauhid

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Rajshahi Univ. of Eng. & Technol., Rajshahi, Bangladesh
  • fYear
    2012
  • fDate
    20-22 Dec. 2012
  • Firstpage
    105
  • Lastpage
    108
  • Abstract
    This paper illustrates on such an intelligent autonomous vehicle (mobile robot) that can be navigated by using visual identification of road direction which utilizes artificial neural network. As a sensor to retrieve the information of surroundings, a camera is mounted on the top of the vehicle. An artificial neural network, Kohonen-type Concurrent Self- Organizing Map (CSOM) is then used to make correct identification of road direction by accessing the sensor´s information. The road directions can be classified into three classes- left, straight & right, for each of which individual SOM module is used. The camera´s readings are fed to all three SOM modules and the winning neuron is selected as output which is then accounted as the classifier´s decision. The decision is then used to navigate the vehicle accordingly.
  • Keywords
    cameras; image sensors; mobile robots; neurocontrollers; path planning; road vehicles; robot vision; self-organising feature maps; CSOM; Kohonen type concurrent self organizing map; artificial neural network; camera; information retrieval; intelligent autonomous vehicle navigation; mobile robot; road direction identification; sensor information; visual identification; Artificial neural networks; Image edge detection; Mobile robots; Navigation; Roads; Vehicles; artificial neural network; autonomous vehicle; concurrent self-organizing map; edge detection; visual road detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrical & Computer Engineering (ICECE), 2012 7th International Conference on
  • Conference_Location
    Dhaka
  • Print_ISBN
    978-1-4673-1434-3
  • Type

    conf

  • DOI
    10.1109/ICECE.2012.6471496
  • Filename
    6471496