基于操作条件反射机制的感觉运动系统认知模型的建立  

Foundation of the Sensorimotor System Cognitive Model with Operant Conditioning Mechanism

作　　者：任红格[1] 史涛[1] 张瑞成[1] 

机构地区：[1]河北联合大学电气工程学院,河北唐山063009

出　　处：《机器人》2012年第3期292-298,共7页Robot

基　　金：国家自然科学基金专项基金资助项目(61040012)

摘　　要：针对运动平衡控制问题,提出了一个基于操作条件反射原理的感觉运动系统认知模型,研究了小脑、基底核、大脑皮质以及其它神经器官工作的协同性,构建了感觉运动系统的认知模型.该认知模型主要由小脑和基底核以及大脑皮质组成,其中:小脑通过监督学习实现状态到行为的感觉运动神经映射;基底核利用行为预测评价结果对动作实施基于操作条件反射原理的概率式选择;而大脑皮质接收并发送有用信号给基底核与小脑,形成了感觉运动系统的闭环反馈回路.本文描述了基于操作条件反射原理的感觉运动系统认知模型的具体结构、功能与算法,并在两轮机器人上进行了仿真实验,再现了机器人类似人或动物的自主学习能力和运动平衡技能.结果表明,该模型具有较强的认知特性,使机器人能通过自主学习掌握运动平衡的控制技能.For the movement balance control, a sensorimotor system cognitive model based on operant conditioning principle is presented, and the cooperation among cerebellum, basal ganglia, cerebral cortex and other nervous organs is studied, so that a cognitive model of sensorimotor system is established. The cognitive model mainly consists of cerebellum, basal ganglia and cerebral cortex. Thereinto, the cerebellum realizes sensorimotor nerve mapping from states to actions by super- vised learning; the basal ganglia implements probabilistic choice of actions based on operant conditioning principle according to action forecast evaluation results; moreover, the cerebral cortex receives and sends useful information to the basal ganglia and cerebellum, consequently, the closed feedback loop of a sensorimotor system is formed. This paper presents concrete structure, function and algorithm of the sensorimotor system cognitive model based on operant conditioning principle, and performs some simulation experiments on the two-wheeled robot which reproduces the self-learning ability and movement balance skill like human or animal. The results indicate that this model has the good cognitive characteristics and can make the robot master the movement balance control skill through self-learning.

关 键 词：感觉运动系统 操作条件反射 认知模型 小脑 基底核 运动平衡控制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]