提出了一种基于模糊粗糙集的非结构化路径识别与机器人引导方法。通过自适应面阵列电荷耦合传感器的图像清晰度控制方法,获取了最佳信息量图像。构建了模糊粗糙集的非结构化路径识别模型,借助粗糙集理论预定义图像目标、背景和不确定区域,融合相对模糊连接度竞争机制对不确定区域的像素进行了模糊重分类,精确描绘了机器人的导航路径。该模型可实现未知非结构化路径区域的自动识别,亦可引入灰度先验特征识别指定路径区域。结果表明,该方法对提高机器人在非结构化环境中的自主探索能力具有实际意义。

An unstructured path recognition and robot vision guidance method based on the fuzzy-rough set is proposed. With the image definition automatic control algorithm based on the self-adaptive surface array charge-coupled device, the images with the best amount of information are obtained. The unstructured path recognition model based on a fuzzy-rough set is built, in which the image target, background and uncertainty area are predefined under the help of the rough set theory and the relative fuzzy connectedness competition mechanism is fused to reclassify the pixels in the uncertain region according to the ambiguity and the robot navigation path is delineated. With this model, the automatic recognition of the unknown and unstructured path areas can be realized, and the gray priori features to recognize the specified path areas can be introduced. The results show that the proposed method has a practical significance for improving the autonomous exploration ability of mobile robots in unstructured environments.