Evolving an Environment Model for Robot Localization

Created by W.Langdon from gp-bibliography.bib Revision:1.4394

  author =       "Marc Ebner",
  title =        "Evolving an Environment Model for Robot Localization",
  booktitle =    "Genetic Programming, Proceedings of EuroGP'99",
  year =         "1999",
  editor =       "Riccardo Poli and Peter Nordin and 
                 William B. Langdon and Terence C. Fogarty",
  volume =       "1598",
  series =       "LNCS",
  pages =        "184--192",
  address =      "Goteborg, Sweden",
  publisher_address = "Berlin",
  month =        "26-27 " # may,
  organisation = "EvoNet",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming: Poster",
  ISBN =         "3-540-65899-8",
  URL =          "http://wwwi2.informatik.uni-wuerzburg.de/mitarbeiter/ebner/research/publications/uniTu/gplocstat.ps.gz",
  URL =          "http://citeseer.ist.psu.edu/395304.html",
  URL =          "http://www.springerlink.com/openurl.asp?genre=article&issn=0302-9743&volume=1598&spage=184",
  DOI =          "doi:10.1007/3-540-48885-5_15",
  size =         "9 pages",
  abstract =     "The use of an evolutionary method for robot
                 localization is explored. We use genetic programming to
                 evolve an inverse function mapping sensor readings to
                 robot locations. This inverse function is an internal
                 model of the environment. The robot senses its
                 environment using dense distance information which may
                 be obtained from a laser range finder. Moments are
                 calculated from the distance distribution. These
                 moments are used as terminal symbols in the evolved
                 function. Arithmetic, trigonometric functions and a
                 conditional statement are used as primitive functions.
                 Using this representation we evolved an inverse
                 function to localize a robot in a simulated office
                 environment. We also analyzed the accuracy of the
                 resulting function. This research was done at the
                 University of Tuebingen, Wilhelm-Schickard-Institute
                 for Computer Science, Computer Architecture (Prof.
  notes =        "EuroGP'99, part of \cite{poli:1999:GP}",

Genetic Programming entries for Marc Ebner