Automated discovery and optimization of large irregular tensegrity structures

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "John Rieffel and Francisco Valero-Cuevas and 
                 Hod Lipson",
  title =        "Automated discovery and optimization of large
                 irregular tensegrity structures",
  journal =      "Computers \& Structures",
  volume =       "87",
  number =       "5-6",
  pages =        "368--379",
  year =         "2009",
  ISSN =         "0045-7949",
  DOI =          "doi:10.1016/j.compstruc.2008.11.010",
  URL =          "",
  keywords =     "genetic algorithms, genetic programming, Tensegrity,
                 Smart structures, Map L-system",
  abstract =     "Tensegrities consist of disjoint struts connected by
                 tensile strings which maintain shape due to pre-stress
                 stability. Because of their rigidity, foldability and
                 deployability, tensegrities are becoming increasingly
                 popular in engineering. Unfortunately few effective
                 analytical methods for discovering tensegrity
                 geometries exist. We introduce an evolutionary
                 algorithm which produces large tensegrity structures,
                 and demonstrate its efficacy and scalability relative
                 to previous methods. A generative representation allows
                 the discovery of underlying structural patterns. These
                 techniques have produced the largest and most complex
                 irregular tensegrities known in the field, paving the
                 way toward novel solutions ranging from space antennas
                 to soft robotics.",

Genetic Programming entries for John Rieffel Francisco Valero-Cuevas Hod Lipson