Research On The Cerebellar Control Model For The Temporal Coordination Of Arm Transport And Hand Preshape

The motor balance of human or animal and the movement control skills are from thecerebellar sensorimotor control system. It is an important research subject for the fields ofcybernetics, robotics and artificial intelligence science that on the basis of neurophysiology andneuroanatomy, simulates and replicates the cerebellar sensorimotor control system for the robots.Firstly, according to the theme above and based on Hoff-Arbib’s theory of the minimum jerk,this paper presents a new cerebellum control model which is able to learn the part of the inversedynamics of the arm. To explore the role of the cerebellum by studying the movement of the armextending. Another purpose is to account for the temporal coordination of arm transport and handpreshape during reach and grasp tasks.Secondly, focus on the simulation for the movement of arm extension. In this paper, thereactions of different neurons in our cerebellar model are recorded during training and learning.The results indicate that the model effectively reduces the error between the planned action andreal acion of the arm. It is obviously that show that the cerebellum is involved in motor learning.At last, takes advantage of the new cerebellum control model to explain the temporalcoordination of hand preshape and arm transport. And it has also been suggested that how thestructure could learn the two key functions of the Hoff-Arbib theory, namely TTG (time to go)evaluation and look-ahead state. By the simulation for two-dimensional motion of arm transportand hand preshape, the results demonstrate that some key features of human reach-graspkinematics obtained by Hoff-Arbib model can be achieved by our cerebellum control model andsome performances are even better. In a word, by learning and training, the model can obtain theaccurate smooth motor trajectory.This paper aims to improve the ability of the cerebellum control model to learn the complexcontrol functions, which is very meaningful for the Artificial Intelligence, Control Science andRobotics.