Autonomous Controller Design for Unmanned Aerial Vehicles using Multi-objective Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{barlow:2004:geccogsw,
  author =       "Gregory J. Barlow",
  title =        "Autonomous Controller Design for Unmanned Aerial
                 Vehicles using Multi-objective Genetic Programming",
  booktitle =    "Proceedings of the Graduate Student Workshop at the
                 2004 Genetic and Evolutionary Computation Conference
                 (GECCO-2004)",
  editor =       "R. Poli and S. Cagnoni and M. Keijzer and E. Costa and 
                 F. Pereira and G. Raidl and S. C. Upton and 
                 D. Goldberg and H. Lipson and E. {de Jong} and J. Koza and 
                 H. Suzuki and H. Sawai and I. Parmee and M. Pelikan and 
                 K. Sastry and D. Thierens and W. Stolzmann and 
                 P. L. Lanzi and S. W. Wilson and M. O'Neill and C. Ryan and 
                 T. Yu and J. F. Miller and I. Garibay and G. Holifield and 
                 A. S. Wu and T. Riopka and M. M. Meysenburg and 
                 A. W. Wright and N. Richter and J. H. Moore and 
                 M. D. Ritchie and L. Davis and R. Roy and M. Jakiela",
  year =         "2004",
  address =      "Seattle, Washington, USA",
  month =        "24-26 " # jun,
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 robotics, multi-objective optimisation, unmanned aerial
                 vehicles",
  URL =          "http://www.cs.bham.ac.uk/~wbl/biblio/gecco2004/WGSW001.pdf",
  URL =          "http://www.andrew.cmu.edu/user/gjb/includes/publications/conference/barlow2004-geccogsw/barlow2004-geccogsw.pdf",
  abstract =     "Autonomous navigation controllers were developed for
                 fixed wing unmanned aerial vehicle (UAV) applications
                 using multi-objective genetic programming (GP). Four
                 fitness functions derived from flight simulations were
                 designed and multi-objective GP was used to evolve
                 controllers able to locate a radar source, navigate the
                 UAV to the source efficiently using on-board sensor
                 measurements, and circle around the emitter.
                 Controllers were evolved for three different kinds of
                 radars: stationary, continuously emitting radars,
                 stationary, intermittently emitting radars, and mobile,
                 continuously emitting radars. In this study, realistic
                 flight parameters and sensor inputs were selected to
                 aid in the transference of evolved controllers to
                 physical UAVs.",
  notes =        "Winner of Best Paper at the Graduate Student Workshop
                 at the 2004 Genetic and Evolutionary Computation
                 Conference (GECCO-2004).
                 http://www-illigal.ge.uiuc.edu:8080/GECCO-2004/awards-winners.html

                 GECCO-2004WKS Distributed on CD-ROM at GECCO-2004",
}

Genetic Programming entries for Gregory J Barlow

Citations