Gait Control Generation for Physically Based Simulated Robots Using Genetic Algorithms

  • Milton Roberto Heinen
  • Fernando Santos Osório
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4140)


This paper describes our studies in the legged robots research area and the development of the LegGen System, that is used to automatically create and control stable gaits for legged robots into a physically based simulation environment. The parameters used to control the robot are optimized using Genetic Algorithms (GA). Comparisons between different fitness functions were accomplished, indicating how to compose a better multi-criterion fitness function to be used in the gait control of the legged robots. The best gait control solution and the best robot model were selected in order to help us to build a real robot in the future. The results also showed that it is possible to generate stable gaits using GA in an efficient manner.


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  1. 1.
    Dudek, G., Jenkin, M.: Computational Principles of Mobile Robotics. Cambridge Univ. Press, Cambridge (2000)MATHGoogle Scholar
  2. 2.
    Wyeth, G., Kee, D., Yik, T.F.: Evolving a locus based gait for a humanoid robot. In: Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), Las Vegas, NV, vol. 2, pp. 1638–1643 (2003)Google Scholar
  3. 3.
    Chernova, S., Veloso, M.: An evolutionary approach to gait learning for four-legged robots. In: Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), Sendai, Japan (2004)Google Scholar
  4. 4.
    Goldberg, D.E.: Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)MATHGoogle Scholar
  5. 5.
    Mitchell, M.: An Introduction to Genetic Algorithms. MIT Press, Cambridge (1996)Google Scholar
  6. 6.
    Darwin, C.: Origin of Species. John Murray, London (1859)Google Scholar
  7. 7.
    Heinen, M.R., Osório, F.S.: Applying genetic algorithms to control gait of physically based simulated robots. In: Proc. IEEE Congr. Evolutionary Computation (CEC), Vancouver, Canada (2006)Google Scholar
  8. 8.
    Holland, J.H.: Adaptation in Natural and Artificial Systems. Univ. Michigan Press, Ann Arbor (1975)Google Scholar
  9. 9.
    Wolff, K., Nordin, P.: Evolutionary learning from first principles of biped walking on a simulated humanoid robot. In: Proc. Advanced Simulation Technologies Conf. (ASTC), Orlando, FL (2003)Google Scholar
  10. 10.
    Golubovic, D., Hu, H.: Ga-based gait generation of sony quadruped robots. In: Proc. 3th IASTED Int. Conf. Artificial Intelligence and Applications (AIA), Benalmadena, Spain (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Milton Roberto Heinen
    • 1
  • Fernando Santos Osório
    • 1
  1. 1.Unisinos – PIPCA – Applied ComputingSão LeopoldoBrazil

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