Hybrid evolutionary designer of modular robots

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Alattas:2016:CT-IETA,

• 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

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