Applying evolutionary optimisation to robot obstacle avoidance

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

  author =       "Olivier Pauplin and Jean Louchet and 
                 Evelyne Lutton and Michel Parent",
  title =        "Applying evolutionary optimisation to robot obstacle
  booktitle =    "ISCIIA, 2004",
  year =         "2004",
  pages =        "20--24",
  address =      "Haikou, China",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 algorithm, stereovision, vision systems for robotics,
                 obstacle detection",
  URL =          "",
  URL =          "",
  hal_id =       "inria-00000494",
  hal_version =  "v1",
  size =         "6 pages",
  abstract =     "This paper presents an artificial evolution-based
                 method for stereo image analysis and its application to
                 real-time obstacle detection and avoidance for a mobile
                 robot. It uses the Parisian approach, which consists
                 here in splitting the representation of the robot's
                 environment into a large number of simple primitives,
                 the flies, which are evolved following a biologically
                 inspired scheme and give a fast, low-cost solution to
                 the obstacle detection problem in mobile robotics.",

Genetic Programming entries for Olivier Pauplin Jean Louchet Evelyne Lutton Michel Parent