Path planning for unmanned aerial vehicles based on genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4192

  author =       "Xiaoyu Yang and Meng Cai and Jianxun Li",
  booktitle =    "2016 Chinese Control and Decision Conference (CCDC)",
  title =        "Path planning for unmanned aerial vehicles based on
                 genetic programming",
  year =         "2016",
  pages =        "717--722",
  abstract =     "Path planning system is one of the key component for
                 the unmanned aerial vehicles (UAVs) and mobile robots
                 in modern operational systems used in all sorts of
                 circumstances. Generally, genetic algorithm (GA) plays
                 a big role in dealing with optimisation problems.
                 However, compared to GA, genetic programming (GP)
                 displays better modelling and optimising ability in
                 path planning problem. GP is capable of dealing with
                 UAV and mobile robot path planning problems. GP
                 improves performance by using generalised hierarchical
                 computer programs and optimising evolutionarily. This
                 paper presents an optimised GP method which applies to
                 path planning problem. Several special designed
                 function and symbol operators are proposed and appended
                 to the binary tree structure, as well as the redesigned
                 decoding system. With the combination of selection and
                 reproduction operation, the optimised GP accomplishes
                 the design of path planning. By using the optimised GP
                 method, experiment results display better fitness paths
                 against GA method.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CCDC.2016.7531079",
  month =        may,
  notes =        "Also known as \cite{7531079}",

Genetic Programming entries for Xiaoyu Yang Meng Cai Jianxun Li