Table of Contents Author Guidelines Submit a Manuscript
Computational Intelligence and Neuroscience
Volume 2016, Article ID 5615618, 13 pages
http://dx.doi.org/10.1155/2016/5615618
Research Article

Quadrupedal Robot Locomotion: A Biologically Inspired Approach and Its Hardware Implementation

1Division of Postgraduate Studies and Research, Leon Institute of Technology, 37290 Leon, GTO, Mexico
2Department of Electronics, DICIS, University of Guanajuato, 36885 Salamanca, GTO, Mexico
3Department of Organizational Studies, DCEA, University of Guanajuato, 36250 Guanajuato, GTO, Mexico
4Division of Postgraduate Studies and Research, Tijuana Institute of Technology, 22414 Tijuana, BC, Mexico

Received 12 February 2016; Revised 6 April 2016; Accepted 24 May 2016

Academic Editor: Ricardo Aler

Copyright © 2016 A. Espinal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. R. J. Full and D. E. Koditschek, “Templates and anchors: neuromechanical hypotheses of legged locomotion on land,” The Journal of Experimental Biology, vol. 202, no. 23, pp. 3325–3332, 1999. View at Google Scholar · View at Scopus
  2. A. J. Ijspeert, “Central pattern generators for locomotion control in animals and robots: a review,” Neural Networks, vol. 21, no. 4, pp. 642–653, 2008. View at Publisher · View at Google Scholar · View at Scopus
  3. H. Kimura, I. Shimoyama, and H. Miura, “Dynamics in the dynamicwalk of a quadruped robot,” International Journal of Robotics Research, vol. 4, no. 2, pp. 187–202, 2003. View at Google Scholar
  4. P. Arena, L. Fortuna, M. Frasca, and G. Sicurella, “An adaptive, self-organizing dynamical system for hierarchical control of bio-inspired locomotion,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, vol. 34, no. 4, pp. 1823–1837, 2004. View at Publisher · View at Google Scholar · View at Scopus
  5. L. H. Scott, “Central pattern generator,” Current Biology, vol. 10, no. 2, pp. 176–177, 2000. View at Google Scholar
  6. C. M. A. Pinto, “Central pattern generator for legged locomotion: a mathematical approach,” in Proceedings of the Workshop on Robotics and Mathematics, vol. 16, pp. 1–6, 2007.
  7. A. Fujii, N. Saito, K. Nakahira, A. Ishiguro, and P. Eggenberger, “Generation of an adaptive controller CPG for a quadruped robot with neuromodulation mechanism,” in Proceedings of the International Conference on Intelligent Robots and Systems (IEEE/RSJ '02), pp. 2619–2624, IEEE, October 2002. View at Scopus
  8. M. Grabowska, E. Godlewska, J. Schmidt, and S. Daun-Gruhn, “Quadrupedal gaits in hexapod animals—inter-leg coordination in free-walking adult stick insects,” The Journal of Experimental Biology, vol. 215, no. 24, pp. 4255–4266, 2012. View at Publisher · View at Google Scholar · View at Scopus
  9. C. Weems and S. Dropsho, “Real-time computing: implications for general microprocessors,” Tech. Rep., University of Massachusetts, 1995. View at Google Scholar
  10. A. Billard and A. J. Ijspeert, “Biologically inspired neural controllers for motor control in a quadruped robot,” in Proceedings of the International Joint Conference on Neural Networks (IJCNN '00), pp. 637–641, July 2000. View at Scopus
  11. Y. Fukuoka, H. Kimura, and A. H. Cohen, “Adaptive dynamic walking of a quadruped robot on irregular terrain based on biological concepts,” The International Journal of Robotics Research, vol. 22, no. 3-4, pp. 187–202, 2003. View at Publisher · View at Google Scholar · View at Scopus
  12. S. Still and M. W. Tilden, “Controller for a four-legged walking machine,” in Neuromorphic Systems Engineering Silicon from Neurobiology, vol. 10 of Progress in Neural Processing, pp. 138–148, World Scientific, Singapore, 1998. View at Publisher · View at Google Scholar
  13. J. Liu and C. Wang, “A survey of neuromorphic engineering—biological nervous systems realized on silicon,” in Proceedings of the IEEE Circuits and Systems International Conference on Testing and Diagnosis (ICTD '09), pp. 1–4, IEEE, Chengdu, China, April 2009. View at Publisher · View at Google Scholar · View at Scopus
  14. H. Soula, G. Beslon, and O. Mazet, “Spontaneous dynamics of asymmetric random recurrent spiking neural networks,” Neural Computation, vol. 18, no. 1, pp. 60–79, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  15. B. Cessac, “A discrete time neural network model with spiking neurons: rigorous results on the spontaneous dynamics,” Journal of Mathematical Biology, vol. 56, no. 3, pp. 311–345, 2008. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  16. X. Yao, “Evolving artificial neural networks,” Proceedings of the IEEE, vol. 87, no. 9, pp. 1423–1447, 1999. View at Publisher · View at Google Scholar · View at Scopus
  17. A. J. Ijspeert, “A connectionist central pattern generator for the aquatic and terrestrial gaits of a simulated salamander,” Biological Cybernetics, vol. 84, no. 5, pp. 331–348, 2001. View at Publisher · View at Google Scholar · View at Scopus
  18. A. J. Ijspeert and J. Kodjabachian, “Evolution and development of a central pattern generator for the swimming of a lamprey,” Artificial Life, vol. 5, no. 3, pp. 247–269, 1999. View at Publisher · View at Google Scholar · View at Scopus
  19. A. Ortega, M. de la Cruz, and M. Alfonseca, “Christiansen grammar evolution: grammatical evolution with semantics,” IEEE Transactions on Evolutionary Computation, vol. 11, no. 1, pp. 77–90, 2007. View at Publisher · View at Google Scholar
  20. Y. Jin, “A comprehensive survey of fitness approximation in evolutionary computation,” Soft Computing, vol. 9, no. 1, pp. 3–12, 2005. View at Publisher · View at Google Scholar
  21. T. Kreuz, D. Chicharro, C. Houghton, R. G. Andrzejak, and F. Mormann, “Monitoring spike train synchrony,” Journal of Neurophysiology, vol. 109, no. 5, pp. 1457–1472, 2013. View at Publisher · View at Google Scholar · View at Scopus
  22. D. Simon, Evolutionary Optimization Algorithms, John Wiley & Sons, 2013. View at MathSciNet