Abstract
Decades of research into the structure and function of the cerebellum
have led to a clear understanding of many of its cells, as well as
how learning takes place. Furthermore, there are many theories on
what signals the cerebellum operates on, and how it works in concert
with other parts of the nervous system. Nevertheless, the application
of computational cerebellar models to the control of robot dynamics
remains in its infant state. To date, a few applications have been
realized, yet limited to the control of traditional robot structures
which, strictly speaking, do not require adaptive control for the
tasks that are performed since their dynamic structures are relatively
simple. The currently emerging family of light-weight robots (Hirzinger,
1996) poses a new challenge to robot control: due to their complex
dynamics traditional methods, depending on a full analysis of the
dynamics of the system, are no longer applicable since the joints
influence each other dynamics during movement. Can artificial cerebellar
models compete here? In this overview paper we present a succinct
introduction of the cerebellum, and discuss where it could be applied
to tackle problems in robotics. Without conclusively answering the
above question, an overview of several applications of cerebellar
models to robot control is given.
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diverse cognitive systems bib
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