Central Pattern Generators for Gait Generation in Bipedal Robots

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

@InCollection{Heralic:2007:hrnd,
  author =       "Almir Heralic and Krister Wolff and Mattias Wahde",
  title =        "Central Pattern Generators for Gait Generation in
                 Bipedal Robots",
  booktitle =    "Humanoid Robots: New Developments",
  publisher =    "I-Tech Education and Publishing",
  year =         "2007",
  editor =       "Armando Carlos {de Pina Filho}",
  chapter =      "17",
  pages =        "285--304",
  month =        jun,
  note =         "Invited book chapter",
  address =      "Vienna, Austria",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-902613-00-4",
  URL =          "http://www.intechopen.com/download/pdf/pdfs_id/237",
  URL =          "http://www.intechopen.com/articles/show/title/central_pattern_generators_for_gait_generation_in_bipedal_robots",
  DOI =          "doi:10.5772/4873",
  abstract =     "An obvious problem confronting humanoid robotics is
                 the generation of stable and efficient gaits. Whereas
                 wheeled robots normally are statically balanced and
                 remain upright regardless of the torques applied to the
                 wheels, a bipedal robot must be actively balanced,
                 particularly if it is to execute a human-like, dynamic
                 gait. The success of gait generation methods based on
                 classical control theory, such as the zero-moment point
                 (ZMP) method (Takanishi et al., 1985), relies on the
                 calculation of reference trajectories for the robot to
                 follow. In the ZMP method, control torques are
                 generated in order to keep the zero-moment point within
                 the convex hull of the support area defined by the
                 feet. When the robot is moving in a well-known
                 environment, the ZMP method certainly works well.
                 However, when the robot finds itself in a dynamically
                 changing real-world environment, it will encounter
                 unexpected situations that cannot be accounted for in
                 advance. Hence, reference trajectories can rarely be
                 specified under such circumstances. In order to address
                 this problem, alternative, biologically inspired
                 control methods have been proposed, which do not
                 require the specification of reference trajectories.
                 The aim of this chapter is to describe one such method,
                 based on central pattern generators (CPGs), for control
                 of bipedal robots.",
  size =         "20 pages",
}

Genetic Programming entries for Almir Heralic Krister Wolff Mattias Wahde

Citations