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- W2117274769 abstract "This paper presents how a plausible cerebellum-like architecture can abstract corrective models in the framework of a robot control task when manipulating objects that significantly affect the dynamics of the system. The presented scheme is adequate to control non-stiff-joint robots with low-power actuators which involve controlling systems with high inertial components. We evaluate the way in which the cerebellum stores a model in the granule layer, how its microstructure can efficiently abstract models and deliver accurate corrective torques for increasing precision during object manipulation. Particularly we study how input sensory-motor representations can enhance model abstraction capabilities during accurate movements, making use of explicit (model-related input labels) and implicit model representations (sensory signals). Finally we focus on how our cerebellum model (using a temporal correlation kernel) properly deals with transmission delays in sensory-motor pathways." @default.
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- W2117274769 date "2010-07-01" @default.
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- W2117274769 title "Cerebellar spiking engine: Towards objet model abstraction in manipulation" @default.
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- W2117274769 doi "https://doi.org/10.1109/ijcnn.2010.5596531" @default.
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