Abstract
The study of how infants strapped in a Jolly Jumper learn to bounce can help clarify how they explore different ways of exploiting the dynamics of their movements. In this paper, we describe and discuss a set of preliminary experiments performed with a bouncing humanoid robot and aimed at instantiating a few computational principles thought to underlie the development of motor skills. Our experiments show that a suitable choice of the coupling constants between hip, knee, and ankle joints, as well as of the strength of the sensory feedback, induces a reduction of movement variability, and leads to an increase in bouncing amplitude and movement stability. This result is attributed to the synergy between neural and body-environment dynamics.
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Lungarella, M., Berthouze, L. (2004). Robot Bouncing: On the Synergy Between Neural and Body-Environment Dynamics. In: Iida, F., Pfeifer, R., Steels, L., Kuniyoshi, Y. (eds) Embodied Artificial Intelligence. Lecture Notes in Computer Science(), vol 3139. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27833-7_6
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DOI: https://doi.org/10.1007/978-3-540-27833-7_6
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