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针对认知机器人的自主学习问题,提出一种基于操作条件反射原理的学习模型(OCLM).该模型采用状态空间、操作行为空间、概率分布函数、仿生学习机制、系统熵等进行描述,给出状态的“负理想度”的概念,定义了取向函数的计算方法.运用模型对机器人避障导航问题进行仿真实验,并对参数设置进行了讨论.实验结果表明,基于OCLM模型的机器人能通过与环境的交互获得认知,成功避障到达目的地,具有一定的自学习能力,从而表明了模型的有效性.
In order to solve the problem of self-learning of cognitive robot, this paper proposes a learning model (OCLM) based on operating principle reflection principle, which is described by state space, operating behavior space, probability distribution function, bionic learning mechanism and system entropy State “negative ideal degree”, and defines the calculation method of orientation function.The model is used to simulate obstacle avoidance navigation of robot and parameter setting is discussed.Experimental results show that robotics based on OCLM model Cognition through interaction with the environment, successful obstacle avoidance reach the destination, has a certain self-learning ability, thus indicating the validity of the model.