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%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