Abstract
The joints of a humanoid robot experience disturbances of markedly different magnitudes during the course of a walking gait. Consequently, simple feedback control techniques poorly track desired joint trajectories. This paper explores the addition of a control system inspired by the architecture of the cerebellum to improve system response. This system learns to compensate the changes in load that occur during a cycle of motion. The joint compensation scheme, called Trajectory Error Learning, augments the existing feedback control loop on a humanoid robot. The results from tests on the GuRoo platform show an improvement in system response for the system when augmented with the cerebellar compensator.
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© 2005 Springer-Verlag Berlin Heidelberg
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Kee, D., Wyeth, G. (2005). Cerebellar Augmented Joint Control for a Humanoid Robot. In: Nardi, D., Riedmiller, M., Sammut, C., Santos-Victor, J. (eds) RoboCup 2004: Robot Soccer World Cup VIII. RoboCup 2004. Lecture Notes in Computer Science(), vol 3276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32256-6_28
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DOI: https://doi.org/10.1007/978-3-540-32256-6_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25046-3
Online ISBN: 978-3-540-32256-6
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