INFANT NEURAL CONTROLLER FOR ADAPTIVE SENSORY MOTOR COORDINATION
INFANT NEURAL CONTROLLER FOR ADAPTIVE SENSORY MOTOR COORDINATION
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DOI：
10.1016/0893-6080(91)90001-l
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发表时间：
1991-01-01
期刊：
影响因子：
7.8
通讯作者：
KUPERSTEIN, M
中科院分区：
文献类型：
--
作者：
KUPERSTEIN, M
这篇综述提出了一种称为INFANT的神经控制器的理论和原型，它可以从自己的经验中学习感觉运动协调。 三个自适应能力进行了讨论：定位固定目标与可移动的传感器，把握任意定位和定向的目标在3D空间与多关节臂，定位一个不可预见的有效载荷准确和稳定的运动，尽管未知的传感器反馈延迟。 婴儿适应身体运动系统的几何形状、控制电路的内部动力学以及物体的位置、方向、形状、重量和大小的不可预见的变化。 它学会准确地抓住一个细长的物体，几乎没有关于物理感觉运动系统几何形状的信息。 这种神经控制器依赖于感觉和运动信号之间的自我一致性来实现无监督学习。 它被设计为通用的协调任何数量的感觉输入与任何数量的关节的肢体。 审查的原则主题是如何相互作用的地形神经领域的各种几何形状可以满足完整的感觉运动电路的自适应行为的约束。
This review presents a theory and prototype for a neural controller called INFANT that learns sensory-motor coordination from its own experience. Three adaptive abilities are discussed: locating stationary targets with movable sensors; grasping arbitrarily positioned and oriented targets in 3D space with multijoint arms, and positioning an unforeseen payload with accurate and stable movements despite unknown sensor feedback delay. INFANT adapts to unforeseen changes in the geometry of the physical motor system, the internal dynamics of the control circuits and to the location, orientation, shape, weight, and size of objects. It learns to accurately grasp an elongated object with almost no information about the geometry of the physical sensory-motor system. This neural controller relies on the self-consistency between sensory and motor signals to achieve unsupervised learning. It is designed to be generalized for coordinating any number of sensory inputs with limbs of any number of joints. The principle theme of the review is how various geometries of interacting topographic neural fields can satisfy the constraints of adaptive behavior in complete sensory-motor circuits.