Learning with a Quadruped Chopstick Robot
Organisms exhibit a close structure-function relationship and a slight change in structure may in turn change their outputs accordingly . This feature is important as it is the main reason why organisms have better malleability than computers in dealing with environmental changes. A quadruped chopstick robot controlled by a biologically-motivated neuromolecular model, named Miky, has been developed. Miky’s skeleton and its four feet were comprised of 16 deposable chopsticks, with each foot being controlled by an actuator (motor). The neuromolecular model is a multilevel neural network which captures the biological structure-function relationship and serves to transform signals sent from its sensors into a sequence of signals in space and time for controlling Miky’s feet (through actuators). The task is to teach Miky to walk, jump, pace, gallop, or make a turn. Our experimental result shows that Miky exhibits a close structure-function relationship that allows it to learn to accomplish these tasks in a continuous manner.
KeywordsEvolutionary learning Robot Neural networks Sensors
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- 3.de Garis, H.: An artificial brain: ATR’s cam-brain project aims to build/evolve an artificial brain with a million neural net modules inside a trillion cell cellular automata machine. New Generation Computing Journal 12, 2 (1994)Google Scholar
- 6.Thompson, A.: Evolving electronic robot controllers that exploit hardware resources. In: Proc. 3rd European Conf. Artificial Life, Granada, Spain, pp. 640–656 (1995)Google Scholar
- 7.Miller, J.F., Downing, K.: Evolution in materio: looking beyond the silicon box. In: Proc. NASA/DoD Conf. Evolvable Hardware, pp. 167–176 (2002)Google Scholar
- 8.Vassilev, V.K., Job, D., Miller, J.F.: Towards the automatic design of more efficient digital circuits. In: Proc. 2nd NASA/DoD Workshop on Evolvable Hardware, Palo Alto, CA, pp. 151–160 (2000)Google Scholar
- 13.Matsumoto, G., Tsukita, S., Arai, T.: Organization of the axonal cytoskeleton: differentiation of the microtubule and actin filament arrays. In: Kinesin, D., Warner, F.D., McIntosh, J.R. (eds.) Cell Movement. Microtubule Dynamics, vol. 2, pp. 335–356. Alan R. Liss, New York (1989)Google Scholar
- 14.Werbos, P.: The cytoskeleton: why it may be crucial to human learning and to neurocontrol. Nanobiology 1, 75–95 (1992)Google Scholar
- 17.Eldredge, N., Gould, S.J.: Punctuated equilibria: an alternative to phyletic gradualism. In: Schopf, T.J.M. (ed.) Models in Paleobiology, pp. 82–115. Freeman, Cooper and Company, San Francisco (1972)Google Scholar