• DocumentCode
    1592893
  • Title

    An improved BP neural network based on GA for 3D laser data repairing

  • Author

    Yu, Shouqian ; Rong, Lixia ; Chen, Weihai ; Wu, Xingming

  • Author_Institution
    Beijing University of Aeronautics & Astronautics
  • fYear
    2008
  • Firstpage
    571
  • Lastpage
    576
  • Abstract
    Affected by scanning object, environment, scanning speed and user¿s operation .etc, some information of the object¿s surface can¿t be detected by the laser scanner. Aiming at the data loss in laser detecting , the paper presents an improved BP neural network based on GA for 3D laser data repairing, the novelty of this method is adopting Genetic Algorithm(GA) to optimize the configure and weight of network, and at the same time combining Back Propagation(BP) Algorithm to find optimal approximation. The simulation shows the improved BP neural network based on GA has a faster constringency speed and better repairing precision than traditional BP neural network and GA algorithm. Lastly, the paper gives the result of repairing the point cloud collected by 3D information reconstruction system using this network
  • Keywords
    Approximation algorithms; Artificial intelligence; Clouds; Genetics; Machine vision; Neural networks; Object detection; Optimization methods; Surface emitting lasers; Turning; Data repairing, GA, BP network, Laser scanner;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics, Automation and Mechatronics, 2008 IEEE Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4244-1675-2
  • Electronic_ISBN
    978-1-4244-1676-9
  • Type

    conf

  • DOI
    10.1109/RAMECH.2008.4690878
  • Filename
    4690878