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A new control model for the temporal coordination of arm transport and hand preshape applying to two-dimensional space

机译:二维空间中手臂运输和手预塑形时间协调的新控制模型

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It is an important research subject for the fields of cybernetics, robotics and artificial intelligence science that on the basis of neurophysiology and neuroanatomy, simulates and replicates the cerebellar sensorimotor control system for the robots. Around this theme and 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 been suggested that how the structure could learn the two key functions required in the Hoff-Arbib theory, namely state look-ahead and TTG (time-to-go) estimation. By the simulation for two-dimensional motion of arm transport and hand preshape, the results demonstrate that some key features of human reach-grasp kinematics obtained by Hoff-Arbib model can be achieved by the cerebellum control model and some performances are even better. In a word, by learning and training, the model can obtain the accurate smooth motor trajectory. (C) 2015 Elsevier B.V. All rights reserved.
机译:在神经生物学和神经解剖学的基础上,模拟和复制机器人的小脑感觉运动控制系统是控制论,机器人技术和人工智能科学领域的重要研究课题。围绕这一主题,基于霍夫和阿比布的最小加速度控制理论,本文提出了一种具有小脑状结构的新控制模型,该模型可以说明伸手和抓握任务期间手臂运输和手预塑形的时间协调性。并且还提出了该结构如何学习霍夫-阿比布理论中要求的两个关键功能,即状态超前和TTG(到达时间)估计。通过对手臂运动和手部预塑形的二维运动进行仿真,结果表明,小脑控制模型可以实现Hoff-Arbib模型获得的人体可抓握运动学的一些关键特征,并且一些性能甚至更好。总之,通过学习和训练,该模型可以获得准确的平滑运动轨迹。 (C)2015 Elsevier B.V.保留所有权利。

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