%A Ganghua Sun
%A Brian Scassellati
%T Exploiting Vestibular Output during Learning
Results in Naturally Curved Reaching Trajectories
%X Teaching a humanoid robot to reach for a
visual target is a complex problem in part because
of the high dimensionality of the control
space. In this paper, we demonstrate a biologically
plausible simplification of the reaching
process that replaces the degrees of freedom
in the neck of the robot with sensory readings
from a vestibular system. We show that
this simplification introduces errors that are
easily overcome by a standard learning algorithm.
Furthermore, the errors that are necessarily
introduced by this simplification result
in reaching trajectories that are curved in the
same way as human reaching trajectories.
%K vestibular system, Nico humanoid robot, reaching trajectory, radial basis function network, degrees-of-freedom problem, developmental robot
%P 71-77
%E Luc Berthouze
%E Fr?d?ric Kaplan
%E Hideki Kozima
%E Hiroyuki Yano
%E J?rgen Konczak
%E Giorgio Metta
%E Jacqueline Nadel
%E Giulio Sandini
%E Georgi Stojanov
%E Christian Balkenius
%V 123
%D 2005
%I Lund University Cognitive Studies
%L cogprints4967

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