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Visibility-based modelling and control for network-based robotics

机译:基于可见性的网络机器人建模与控制

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We present an algorithm to model 3D workspace and to understand test scene for navigation or human computer interaction in network-based mobile robot. This was done by line-based modelling and recognition algorithm. Line-based recognition using 3D lines has been tried by many researchers however its reliability still needs improvement due to ambiguity of 3D line feature information from original images. To improve the outcome, we approach firstly to find real planes using the given 3D lines and then to implement recognition process. The methods we use are principle component analysis (PCA), plane sweep, visibility test, and iterative closest point (ICP). During the implementation, we also use 3D map information for localization. We apply this algorithm to real test scene images and to find out our result can be useful to identify doors or walls in indoor environment with better efficiency.
机译:我们提出了一种算法,可对3D工作区建模并了解基于网络的移动机器人中导航或人机交互的测试场景。这是通过基于行的建模和识别算法完成的。许多研究人员已经尝试过使用3D线进行基于线的识别,但是由于来自原始图像的3D线特征信息的歧义性,其可靠性仍需要改进。为了改善结果,我们首先使用给定的3D线找到实际平面,然后实施识别过程。我们使用的方法是主成分分析(PCA),平面扫描,可见性测试和迭代最近点(ICP)。在实施过程中,我们还将3D地图信息用于本地化。我们将该算法应用于真实的测试场景图像,并发现我们的结果可用于以更高的效率识别室内环境中的门或墙。

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