Autonomous Robots

, Volume 11, Issue 3, pp 221–226 | Cite as

Certain Principles of Biomorphic Robots

  • M. Anthony Lewis
  • Lucia S. Simó
Article

Abstract

The field of biomorphic robotics can advance as quickly as clear principles of biological systems can be identified, implemented, and tested in robotic devices. Here, we describe the implementation of three principles: (1) the prediction of the sensory consequences of movement and its role in the extraction of novelty and awareness; (2) learning affordances and the direct perception of what an agent can do at a particular instant and how it can do it; (3) exploitation of the physical dynamics of a system to simplify robot control.

walking machines visuomotor control central pattern generator action oriented perception biomorphic robots biomimetics 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Arbib, M.A. 1997. From visual affordances in monkey parietal cortex to hippocampo-parietal interactions underlying rat navigation. Philos Trans R Soc Lond B Biol Sci, 352:1429–1436.Google Scholar
  2. Bastian, J. 1998. Modulation of calcium-dependent postsynaptic depression contributes to an adaptive sensory filter. J. Neurophysiol, 80(6):3352–3355.Google Scholar
  3. Blakemore, S.-J., Wolpert, D.M., and Frith, C.D. 1999. The cerebellum contributes to somatosensory cortical activity during self-produced tactile stimulation. NeuroImage, 10:448–459.Google Scholar
  4. Collins, S.H., Wisse, M., and Ruina, A. 2001. A3-D passive-dynamic walking robot with two legs and knees. International Journal of Robotics Research, in press.Google Scholar
  5. Gibson, J.J. 1986. The Ecological Approach to Visual Perception, Lawrence Erlbaum Assoc.: London.Google Scholar
  6. Kimura, H., Akiyama, S., and Sakurama, K. 1999. Realization of dynamic walking and running of the quadruped using neural oscillator. Autonomous Robots, 7(3).Google Scholar
  7. Lewis, M.A. and Simó, L.S. 1999. Elegant stepping: A model of visually triggered gait adaptation connection. Science, 11(3–4): 331–344.Google Scholar
  8. Lewis, M.A., Etienne-Cummings, R., Hartmann, M.J., and Cohen, A.H. 2000. Toward biomorphic control using custom a VLSI chips. 2000 International Conference on Robotics and Automation, San Francisco.Google Scholar
  9. McGeer, T. 1990. Passive dynamic walking. International Journal of Robotics Research, 9(2):62–82.Google Scholar
  10. Pratt, J. and Pratt, G. 1999. Exploiting natural dynamics in the control of a 3D bipedal walking simulation. In Proceedings of the International Conference on Climbing andWalking Robots (CLAWAR99), Portsmouth, UK.Google Scholar
  11. Sutton, R.S. and Barto, A.G. 1998. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning), Cambridge: MIT Press.Google Scholar
  12. Warren, W.H. 1984. Perceiving affordances: Visual guidance of stair climbing. J. Experimental Psychology: Human Perception and Performance, 10(5):683–703.Google Scholar
  13. Widrow, B. and Hoff, M.F. 1960. Adaptive switching circuits. In 1960 IRE Wescon Convention Record, part 4, pp. 96–104.Google Scholar

Copyright information

© Kluwer Academic Publishers 2001

Authors and Affiliations

  • M. Anthony Lewis
    • 1
  • Lucia S. Simó
    • 1
  1. 1.Iguana Robotics, Inc.MahometUSA

Personalised recommendations