Hybrid evolutionary designer of modular robots

Created by W.Langdon from gp-bibliography.bib Revision:1.4221

  author =       "R. Alattas",
  booktitle =    "2016 Annual Connecticut Conference on Industrial
                 Electronics, Technology Automation (CT-IETA)",
  title =        "Hybrid evolutionary designer of modular robots",
  year =         "2016",
  abstract =     "The majority of robotic design approaches start with
                 designing morphology, then designing the robot control.
                 Even in evolutionary robotics, the morphology tends to
                 be fixed while evolving the robot control, which
                 considered insufficient since the robot control and
                 morphology are interdependent. Moreover, both control
                 and morphology are highly interdependent with the
                 surrounding environment, which affects the used
                 optimisation strategies. Therefore, we propose in this
                 paper a novel hybrid GP/GA method for designing
                 autonomous modular robots that co-evolves the robot
                 control and morphology and also considers the
                 surrounding environment to allow the robot of achieving
                 behaviour specific tasks and adapting to the
                 environmental changes. The introduced method is
                 automatically designing feasible robots made up of
                 various modules. Then, our new evolutionary designer is
                 evaluated using a benchmark problem in modular
                 robotics, which is a walking task where the robot has
                 to move a certain distance.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/CT-IETA.2016.7868256",
  month =        oct,
  notes =        "Also known as \cite{7868256}",

Genetic Programming entries for R Alattas