Abstract
Based on Hoff and Arbib' s control theory of the minimum jerk, this paper presents a new control model with cerebellar-like structure which can account for the temporal coordination of arm transport and hand preshape during reach and grasp tasks. And it has also be suggested that how the structure could learn two key functions required in the Hoff-Arbib theory, namely state look-ahead and TTG (time-to-go) estimation. The simulation results demonstrate that whether it be in a d or 2 d space, by training and learning, the model can obtain the accurate smooth motor trajectory.
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