Generative Representations for the Automated Design of Modular Physical Robots

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

@Article{hornby:2003:tRA,
  author =       "Gregory S. Hornby and Hod Lipson and 
                 Jordan B. Pollack",
  title =        "Generative Representations for the Automated Design of
                 Modular Physical Robots",
  journal =      "IEEE transactions on Robotics and Automation",
  year =         "2003",
  volume =       "19",
  number =       "4",
  pages =        "709--713",
  month =        aug,
  keywords =     "genetic algorithms, genetic programming, Design
                 automation, evolutionary robotics, generative
                 representations, Lindenmayer systems",
  ISSN =         "1042-296X",
  URL =          "http://ccsl.mae.cornell.edu/papers/ITRA03_Hornby.pdf",
  URL =          "http://ieeexplore.ieee.org/iel5/70/27428/01220719.pdf?isnumber=27428&arnumber=1220719",
  DOI =          "doi:10.1109/TRA.2003.814502",
  size =         "17 pages",
  abstract =     "The field of evolutionary robotics has demonstrated
                 the ability to automatically design the morphology and
                 controller of simple physical robots through synthetic
                 evolutionary processes. However, it is not clear if
                 variation-based search processes can attain the
                 complexity of design necessary for practical
                 engineering of robots. Here, we demonstrate an
                 automatic design system that produces complex robots by
                 exploiting the principles of regularity, modularity,
                 hierarchy, and reuse. These techniques are already
                 established principles of scaling in engineering design
                 and have been observed in nature, but have not been
                 broadly used in artificial evolution. We gain these
                 advantages through the use of a generative
                 representation, which combines a programmatic
                 representation with an algorithmic process that
                 compiles the representation into a detailed
                 construction plan. This approach is shown to have two
                 benefits: it can reuse components in regular and
                 hierarchical ways, providing a systematic way to create
                 more complex modules from simpler ones; and the evolved
                 representations can capture intrinsic properties of the
                 design space, so that variations in the representations
                 move through the design space more effectively than
                 equivalent-sized changes in a nongenerative
                 representation. Using this system, we demonstrate for
                 the first time the evolution and construction of
                 modular, three-dimensional, physically moving robots,
                 comprising many more components than previous work on
                 body-brain evolution.",
  notes =        "INSPEC Accession Number: 7719817",
}

Genetic Programming entries for Gregory S Hornby Hod Lipson Jordan B Pollack

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