视觉导航中基于模糊神经网的消阴影算法研究  

Shadow Eliminating Algorithm with Fuzzy Neural Network in Vision Based Navigation

作　　者：郭木河[1,2] 杨磊[1,2] 陶西平[1,2] 何克忠 张钹[1,2] 

机构地区：[1]清华大学计算机科学与技术系 [2]清华大学智能技术与系统国家重点实验室

出　　处：《软件学报》1999年第2期155-159,共5页Journal of Software

摘　　要：在实际的应用中，由于室外移动机器人面临着复杂的环境，道路中充满阴影、水迹等环境噪声．这些噪声严重地损害了以往的各种视觉导航算法的鲁棒性．提出了一种新的面向室外移动机器人导航的阴影消除算法．详述了使用模糊神经网在低分辨率图像上对阴影进行识别，利用遗传算法进行网络结构优化，最后消除原始图像中阴影的方法和过程．同时给出了利用该算法在ＴＨＭＲＩＩ室外移动机器人上进行的实验结果．In past decades, there are many vision algorithms. In practice, the environment in which robot stayed is filled with stochastic noise such as shadow, puddle, and fallen leaves. Those factors damage the robustness of the past vision navigation algorithm. A new method to eliminate shadow during mobile robot navigation is presented in this paper. The presented method gives a detailed description on how to use fuzzy network to recognize and eliminate the shadow in low resolution image during robot navigation, and optimize the structure of fuzzy neural network by genetic algorithm. Also, the experiment results obtained on THMRIII Mobile robot test bed are given in this paper.

关 键 词：消阴影 视觉导航 模糊神经网 机器人视觉系统 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置] TP18[自动化与计算机技术—控制科学与工程]