Skip to main content
Log in

Certain Principles of Biomorphic Robots

  • Published:
Autonomous Robots Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • 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 

  • Bastian, J. 1998. Modulation of calcium-dependent postsynaptic depression contributes to an adaptive sensory filter. J. Neurophysiol, 80(6):3352–3355.

    Google Scholar 

  • 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 

  • 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.

  • Gibson, J.J. 1986. The Ecological Approach to Visual Perception, Lawrence Erlbaum Assoc.: London.

    Google Scholar 

  • Kimura, H., Akiyama, S., and Sakurama, K. 1999. Realization of dynamic walking and running of the quadruped using neural oscillator. Autonomous Robots, 7(3).

  • 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 

  • 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.

  • McGeer, T. 1990. Passive dynamic walking. International Journal of Robotics Research, 9(2):62–82.

    Google Scholar 

  • 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.

  • Sutton, R.S. and Barto, A.G. 1998. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning), Cambridge: MIT Press.

    Google Scholar 

  • Warren, W.H. 1984. Perceiving affordances: Visual guidance of stair climbing. J. Experimental Psychology: Human Perception and Performance, 10(5):683–703.

    Google Scholar 

  • Widrow, B. and Hoff, M.F. 1960. Adaptive switching circuits. In 1960 IRE Wescon Convention Record, part 4, pp. 96–104.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lewis, M.A., Simó, L.S. Certain Principles of Biomorphic Robots. Autonomous Robots 11, 221–226 (2001). https://doi.org/10.1023/A:1012430821608

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1012430821608

Navigation