• DocumentCode
    2480406
  • Title

    A Geometric Radial Basis Function Network for Robot Perception and Action

  • Author

    Vázquez-Santacruz, E. ; Bayro-Corrochano, E.

  • Author_Institution
    CINVESTAV Unidad Guadalajara, Zapopan, Mexico
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    2961
  • Lastpage
    2964
  • Abstract
    This paper presents a new hyper complex valued Radial Basis Network. This network constitutes a generalization of the standard real valued RBF. This geometric RBF can be used in real time to estimate changes in linear transformations between sets of geometric entities. Experiments using stereo image sequences validate this proposal. We propose a Geometric RBF Network (GRBF-N) designed in the geometric algebra framework. We present an application to estimate linear transformations between sets of geometric entities. Our experiments validate our proposal.
  • Keywords
    control engineering computing; image sequences; radial basis function networks; robot vision; stereo image processing; geometric entities; geometric radial basis function network; hypercomplex valued radial basis network; robot action; robot perception; standard real valued RBF; stereo image sequences; Algebra; Argon; Artificial neural networks; Blades; Radial basis function networks; Rotors; Training; RBF; geometric algebra; geometric computing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.725
  • Filename
    5595931