@misc{cogprints4967,
          volume = {123},
          editor = {Luc Berthouze and Fr{\'e}d{\'e}ric Kaplan and Hideki Kozima and Hiroyuki Yano and J{\"u}rgen Konczak and Giorgio Metta and Jacqueline Nadel and Giulio Sandini and Georgi Stojanov and Christian Balkenius},
           title = {Exploiting Vestibular Output during Learning
Results in Naturally Curved Reaching Trajectories},
          author = {Ganghua Sun and Brian Scassellati},
       publisher = {Lund University Cognitive Studies},
            year = {2005},
           pages = {71--77},
        keywords = {vestibular system, Nico humanoid robot, reaching trajectory, radial basis function network, degrees-of-freedom problem, developmental robot},
             url = {http://cogprints.org/4967/},
        abstract = {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.}
}

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