RoboGen: Robot Generation through Artificial Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Auerbach:2014:ALIFE,
  author =       "Joshua E. Auerbach and Deniz Aydin and 
                 Andrea Maesani and Przemyslaw M. Kornatowski and Titus Cieslewski and 
                 Gregoire Heitz and Pradeep R. Fernando and 
                 Ilya Loshchilov and Ludovic Daler and Dario Floreano",
  title =        "{RoboGen}: Robot Generation through Artificial
                 Evolution",
  booktitle =    "Proceedings of the Fourteenth International Conference
                 of the Synthesis and Simulation of Living Systems,
                 ALIFE 14",
  year =         "2014",
  editor =       "Hiroki Sayama and John Rieffel and Sebastian Risi and 
                 Rene Doursat and Hod Lipson",
  series =       "Complex Adaptive Systems",
  pages =        "136--137",
  address =      "New York",
  month =        "30 " # jul # "-2 " # aug,
  organisation = "International Society for Artificial Life",
  publisher =    "MIT Press",
  keywords =     "genetic algorithms, genetic programming, RoboGen",
  isbn13 =       "9780262326216 ?",
  URL =          "http://mitpress.mit.edu/sites/default/files/titles/content/alife14/ch022.html",
  DOI =          "doi:10.7551/978-0-262-32621-6-ch022",
  size =         "2 pages",
  abstract =     "Science instructors from a wide range of disciplines
                 agree that hands-on laboratory components of courses
                 are pedagogically necessary (Freedman, 1997). However,
                 certain shortcomings of current laboratory exercises
                 have been pointed out by several authors (Mataric,
                 2004; Hofstein and Lunetta, 2004). The overarching
                 theme of these analyses is that hands-on components of
                 courses tend to be formulaic, closed-ended, and at
                 times outdated. To address these issues, we envision a
                 novel platform that is not only a didactic tool but is
                 also an experimental testbed for users to play with
                 different ideas in evolutionary robotics (Nolfi and
                 Floreano, 2000), neural networks, physical simulation,
                 3D printing, mechanical assembly, and embedded
                 processing.

                 Here, we introduce RoboGen an open-source software and
                 hardware platform designed for the joint evolution of
                 robot morphologies and controllers a la Sims (1994);
                 Lipson and Pollack (2000); Bongard and Pfeifer (2003).
                 Robo-Gen has been designed specifically to allow
                 evolved robots to be easily manufactured via widely
                 available desktop 3D-printers, and the use of simple,
                 open-source, low-cost, off-the-shelf electronic
                 components. RoboGen features an evolution engine
                 complete with a physics simulator, as well as utilities
                 both for generating design files of body components for
                 3D printing, and for compiling neural-network
                 controllers to run on an Arduino microcontroller
                 board.

                 In this paper, we describe the RoboGen platform, and
                 provide some metrics to assess the success of using it
                 as the hands-on component of a masters-level
                 bio-inspired artificial intelligence course.",
  notes =        "Laboratory of Intelligent Systems Ecole Polytechnique
                 Federale de Lausanne. ALIFE 14
                 http://mitpress.mit.edu/books/artificial-life-14
                 ALIFE14NYC@gmail.com",
}

Genetic Programming entries for Joshua E Auerbach Deniz Aydin Andrea Maesani Przemyslaw M Kornatowski Titus Cieslewski Gregoire Heitz Pradeep R Fernando Ilya Loshchilov Ludovic Daler Dario Floreano

Citations