A Soft-Body Controller with Ubiquitous Sensor Feedback

  • Alexander S. Boxerbaum
  • Kathryn A. Daltorio
  • Hillel J. Chiel
  • Roger D. Quinn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7375)


In this paper, we investigate control architectures that combine implicit models of behavior with ubiquitous sensory input, for soft hyper-redundant robots. Using a Wilson-Cowan neuronal model in a continuum arrangement that mirrors the arrangement of muscles in an earthworm, we can create a wide range of steady waves with descending signals. Here, we demonstrate how sensory feedback from individual segment strains can be used to modulate the behavior in desirable ways.


Strain Sensor Nonlinear Spring Peristaltic Motion Excitatory Connection Snake Robot 
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  1. 1.
    Ostrowski, J., Burdick, J.: Gait Kinematics for a Serpentine Robot. In: Proc. IEEE Int. Conf. Robotics and Automation (ICRA), Minneapolis, MN, vol. 2, pp. 1294–1299 (1996)Google Scholar
  2. 2.
    Hannan, M.W., Walker, I.D.: Analysis and Initial Experiments for a Novel Elephant’s Trunk Robot. In: Proc. IEEE Int. Conf. Intelligent Robots and Systems (IROS), pp. 330–337 (2000)Google Scholar
  3. 3.
    Menciassi, A., Gorini, A., Pernorio, G., Dario, P.: A SMA Actuated Artificial Earthworm. In: Proc. Int. Conf. Robotics and Automation, ICRA (2004)Google Scholar
  4. 4.
    Tsakiris, D.P., Sfakiotakis, M., Menciassi, A., La Spina, G., Dario, P.: Polchaete-like Undulatory Robotic Locomotion. In: Proc. IEEE Int. Conf. Robotics and Automation (ICRA), Barcelona, Spain, pp. 3018–3023 (2005)Google Scholar
  5. 5.
    Trimmer, B., Takesian, A., Sweet, B.: Caterpillar locomotion: a new model for soft-bodied climbing and burrowing robots. In: Proc. 7th Int. Symp. Technology and the Mine Problem, Monterey, CA (2006)Google Scholar
  6. 6.
    Wang, K., Yan, G.: Micro robot prototype for colonoscopy and in vitro experiments. J. Med. Eng. & Tech. 31(1), 24–28 (2007)CrossRefGoogle Scholar
  7. 7.
    Omori, H., Nakamura, T., Yada, T.: An underground explorer robot based on peristaltic crawling of earthworm. Industrial Robot 36(4), 358–364 (2009)CrossRefGoogle Scholar
  8. 8.
    Hirose, S.: Biologically Inspired Robots: Snake-Like Locomotors and Manipulators. Oxford University Press, Oxford (1993)Google Scholar
  9. 9.
    Hatton, R.L., Choset, H.: Generating gaits for snake robots: annealed chain fitting and keyframe wave extraction. Auton. Robot. 28, 271–281 (2010)CrossRefGoogle Scholar
  10. 10.
    Ijspeert, A.J., Crespi, A., Ryczko, D., Cabelguen, J.M.: From swimming to walking with a salamander robot driven by a spinal cord model. Science 315(5817), 1416–1420 (2007)CrossRefGoogle Scholar
  11. 11.
    Brusca, R.C., Brusca, G.J.: Invertebrates. Sinauer Associates, SunderlandGoogle Scholar
  12. 12.
    Ekeberg, Ö., Griller, S.: Simulations of neuromuscular control in lamprey swimming. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 354, 895–902 (1999)CrossRefGoogle Scholar
  13. 13.
    Quillin, K.J.: Kinematic scaling of locomotion by hydrostatic animals: ontogeny of peristaltic crawling by the earthworm lumbricusterrestris. J. Exp. Biol. 202, 661–674 (1999)Google Scholar
  14. 14.
    Boxerbaum, A.S., Chiel, H.J., Quinn, R.D.: Continuous Wave Peristaltic Locomotion. International Journal of Robotics Research (January 2012)Google Scholar
  15. 15.
    Boxerbaum, A.S., Chiel, H.J., Quinn, R.D.: A New Theory and Methods for Creating Peristaltic Motion in a Robotic Platform. In: Proc. Int. Conf. Robotics and Automation (ICRA), pp. 1221–1227 (2010)Google Scholar
  16. 16.
    Quinn, R.D., Nelson, G.M., Ritzmann, R.E., Bachmann, R.J., Kingsley, D.A., Offi, J.T., Allen, T.J.: Parallel Strategies for Implementing Biological Principles Into Mobile Robots. Int. J. Robotics Research 22(3), 169–186 (2003)CrossRefGoogle Scholar
  17. 17.
    Mangan, E.V., Kingsley, D.A., Quinn, R.D., Chiel, H.J.: Development of a peristaltic endoscope. In: Proc. IEEE Int. Conf. Robotics and Automation (ICRA), pp. 347–352 (2002)Google Scholar
  18. 18.
    Ayers, J., Cricket, W., Chris, O.: Lamprey Robots. In: Proc. Int. Symp. Aqua Biomechanisms (2000)Google Scholar
  19. 19.
    Zhang, D., Hu, D., Shen, L., Xie, H.: Design of an artificial bionic neural network to control fish-robot’s locomotion. Neurocomputing 71, 648–654 (2008)CrossRefGoogle Scholar
  20. 20.
    Ijspeert, A.J.: Central pattern generators for locomotion control in animals and robots: A review. Neural Networks 21, 642–653 (2008)CrossRefGoogle Scholar
  21. 21.
    Matsuo, T., Yokoyama, T., Ueno, D., Ishii, K.: Biomimetic Motion Control System Based on a CPG for an Amphibious Multi-Link Mobile Robot. J. Bionic Eng. Suppl., 91–97 (2008)Google Scholar
  22. 22.
    Wadden, T., Hellgren, J., Lansner, A., Grillner, S.: Intersegmental coordination in the lamprey: simulations using a network model without segmental boundaries. Biol. Cybernetics 76, 1–9 (1997)CrossRefGoogle Scholar
  23. 23.
    Boyle, J., Berri, S., Cohen, N.: Gait Modulation in C. Elegans: An Integrated Neuromechanical Model. Frontiers in Computational Neuroscience (March 2012)Google Scholar
  24. 24.
    Moore, A.R.: Muscle tension and reflexes in earthworm. Journal of General Physiology 5, 327 (1923)CrossRefGoogle Scholar
  25. 25.
    Gray, J., Lissmann, W.: Studies in Animal Locomotion VII: Locomotory reflexes in the Earthworm. Journal of Experimental Biology 15, 506–517Google Scholar
  26. 26.
    Collier, H.: Central nervious activity in the earthworm. Journal of Experimental Biology (1939)Google Scholar
  27. 27.
    Boxerbaum, A.S., Horchler, A.D., Shaw, K., Chiel, H.J., Quinn, R.D.: A Controller for Continuous Wave Peristaltic Locomotion. In: International Conference on Intelligent Robots and Systems, IROS (2011)Google Scholar
  28. 28.
    Wilson, H.R., Cowan, J.D.: Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons. Biophys. J. 12, 1–24 (1972)CrossRefGoogle Scholar
  29. 29.
    Ermentrout, G.B., Cowan, J.D.: A Mathematical Theory of Visual Hallucination Patterns. Biol. Cybernetics 34, 137–150 (1979)MathSciNetzbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Alexander S. Boxerbaum
    • 1
  • Kathryn A. Daltorio
    • 1
  • Hillel J. Chiel
    • 2
  • Roger D. Quinn
    • 1
  1. 1.Department of Mechanical and Aerospace EngineeringCase Western Reserve UniversityClevelandUSA
  2. 2.Departments of Biology, Neurosciences, and Biomedical EngineeringCase Western Reserve UniversityClevelandUSA

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