研究复杂多变环境下自主机器人的决策控制.为了提高机器人的适应能力,对机器人特性进行了深入分析,提出了通过模拟人类自我意识在机器人上面建立自我意识来提高机器人的自主性的新思路.首先建立机器人自我意识的模糊推理模型,输出就是当前状态下机器人的自我意识,然后输入到CMAC网络中进行学习,最终改善机器人的综合性能.通过对建立的模型进行Matlab仿真实验证明了这种方法的有效性,为提高自主机器人的控制性能提供了新的方法.%This paper focuses on the decision -making of autonomous robots in complex and changeable environment. In order to improve the a-daptability of the robots, the paper analyzes the characteristics of autonomous robots in depth,and presents an new idea about improving the autonomy of the robot by building self - awareness through the simulation human consciousness. First, the robot self - awareness fuzzy reasoning model is established, the output is the robot self -awareness of the current state, then input it to the CMAC network for learning, eventually the comprehensive performance of the robot can be improved. The effectiveness of the approach is proved through the Matlab simulation results of the model, and provides a new method for improving the control performance of autonomous robot.
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