Variational Genetic Programming for Optimal Control System Synthesis of Mobile Robots

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@Article{Diveev:2015:IFAC-PapersOnLine,

• 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 = "http://www.sciencedirect.com/science/article/pii/S2405896315026427",
• 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 vehicles",

}

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

Citations