Variational Genetic Programming for Optimal Control System Synthesis of Mobile Robots

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  author =       "A. I. Diveev and S. I. Ibadulla and 
                 N. B. Konyrbaev and E. Yu. Shmalko",
  title =        "Variational Genetic Programming for Optimal Control
                 System Synthesis of Mobile Robots",
  journal =      "IFAC-PapersOnLine",
  volume =       "48",
  number =       "19",
  pages =        "106--111",
  year =         "2015",
  note =         "11th IFAC Symposium on Robot Control SYROCO 2015
                 Salvador, Brazil, 26-28 August 2015",
  ISSN =         "2405-8963",
  DOI =          "doi:10.1016/j.ifacol.2015.12.018",
  URL =          "",
  abstract =     "The paper focuses on the problem of autonomous control
                 system synthesis for the mobile robot. The proposed
                 numerical solution is based on a new method of symbolic
                 regression called variational genetic programming. This
                 method uses the principle of variations of the basic
                 solution. An optimal solution is searched over the set
                 of small variations of the given basic solution. Such
                 approach allows to generate automatically a control
                 function that describes the feedback controller. In the
                 given example the control system is synthesized using
                 variational genetic programming for the unmanned mobile
                 robot that has to move to some terminal position from
                 the different initial states avoiding obstacles.",
  keywords =     "genetic algorithms, genetic programming, robust robot
                 control, learning robot control, mobile robots and

Genetic Programming entries for Askhat Diveev Ibraghimovich S I Ibadulla N B Konyrbaev E Yu Shmalko