The current research progresses and problems of the semantic Web are analyzed in this paper, and the insufficiency of using description logic to act as logical foundation for the semantic Web is analyzed too. Accordin...The current research progresses and problems of the semantic Web are analyzed in this paper, and the insufficiency of using description logic to act as logical foundation for the semantic Web is analyzed too. According to the characteristics and requirement of the semantic Web, a kind of new dynamic description logic (DDL) framework is presented. The representation and reasoning of static knowledge and dynamic knowledge are integrated in this framework. Especially, a kind of action description method is proposed, and according to description logic theory, the action semantics is described, so DDL is a kind of formal logical framework which can process static knowledge and dynamic knowledge. The DDL has clear and formally defined semantics. It provides decidable reasoning services, and it can support effective representation and reasoning of the static knowledge, dynamic process and running mechanism (realization and subsumption relation of action). Therefore, the DDL provides reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using description logic to act as logical foundation for the semantic Web.展开更多
视觉SLAM(Simultaneous Localization And Mapping,同时定位与建图)是移动机器人领域的核心技术,传统视觉SLAM还难以适用于高动态场景并且地图中缺少语义信息。提出一种动态环境语义SLAM方法,用深度学习网络对图像进行目标检测,检测动...视觉SLAM(Simultaneous Localization And Mapping,同时定位与建图)是移动机器人领域的核心技术,传统视觉SLAM还难以适用于高动态场景并且地图中缺少语义信息。提出一种动态环境语义SLAM方法,用深度学习网络对图像进行目标检测,检测动态目标所在区域,对图像进行特征提取并剔除动态物体所在区域的特征点,利用静态的特征点进行位姿计算,对关键帧进行语义分割,在构建语义地图时滤除动态物体的地图点构建出无动态物体干扰的语义地图。在TUM数据集上进行实验,结果显示该方法在动态环境下可以提升88.3%位姿估计精度,并且可同时构建出无动态物体干扰的语义地图。展开更多
基金This work was supported by the 863 High Tech Programme(Grant No.2001AA113121)the National Natural Science Foundation of China(Grant No.90104021).
文摘The current research progresses and problems of the semantic Web are analyzed in this paper, and the insufficiency of using description logic to act as logical foundation for the semantic Web is analyzed too. According to the characteristics and requirement of the semantic Web, a kind of new dynamic description logic (DDL) framework is presented. The representation and reasoning of static knowledge and dynamic knowledge are integrated in this framework. Especially, a kind of action description method is proposed, and according to description logic theory, the action semantics is described, so DDL is a kind of formal logical framework which can process static knowledge and dynamic knowledge. The DDL has clear and formally defined semantics. It provides decidable reasoning services, and it can support effective representation and reasoning of the static knowledge, dynamic process and running mechanism (realization and subsumption relation of action). Therefore, the DDL provides reasonable logic foundation for the semantic Web, and overcomes the insufficiency of using description logic to act as logical foundation for the semantic Web.
文摘视觉SLAM(Simultaneous Localization And Mapping,同时定位与建图)是移动机器人领域的核心技术,传统视觉SLAM还难以适用于高动态场景并且地图中缺少语义信息。提出一种动态环境语义SLAM方法,用深度学习网络对图像进行目标检测,检测动态目标所在区域,对图像进行特征提取并剔除动态物体所在区域的特征点,利用静态的特征点进行位姿计算,对关键帧进行语义分割,在构建语义地图时滤除动态物体的地图点构建出无动态物体干扰的语义地图。在TUM数据集上进行实验,结果显示该方法在动态环境下可以提升88.3%位姿估计精度,并且可同时构建出无动态物体干扰的语义地图。
