This site has been permanently archived. This is a static copy provided by the University of Southampton.
TY - GEN
ID - cogprints1322
UR - http://cogprints.org/1322/
A1 - van der Smagt, Patrick
Y1 - 1998///
N2 - 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 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on a full analysis of the dynamics of the system, are no longer
applicable since the joints influence each other dynamics during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.
KW - cerebellum
KW - robot dynamics
KW - robot arm control
KW -
computational cerebellar models
KW - neural networks
TI - Cerebellar control of robot arms
SP - 301
AV - public
EP - 320
ER -