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Collapsible cubes: Removing overhangs from 3D point clouds to build local navigable elevation maps

机译:可折叠立方体:从3D点云中移除悬垂以构建局部通航的高程地图

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摘要

Elevation maps offer a compact 2 1/2 dimensional model of terrain surface for navigation in field mobile robotics. However, building these maps from 3D raw point clouds con- taining overhangs, such as tree canopy or tunnels, can produce useless results. This paper proposes a simple processing of a ground-based point cloud that identifies and removes overhang points that do not constitute an obstacle for navigation while keeping vertical structures such as walls or tree trunks. The procedure uses efficient data structures to collapse unsupported 3D cubes down to the ground. This method has been successfully applied to 3D laser scans taken from a mobile robot in outdoor environments in order to build local elevation maps for navigation. Computation times show an improvement with respect to a previous point-based solution to this problem.
机译:高程图提供了一个紧凑的2 1/2维地形表面模型,可在野外移动机器人中导航。但是,从包含悬挑的3D原始点云(例如树冠或隧道)构建这些地图可能会产生无用的结果。本文提出了一种基于地面的点云的简单处理方法,该方法可以识别并删除不构成导航障碍的悬垂点,同时保留诸如墙壁或树干等垂直结构。该过程使用高效的数据结构将不受支持的3D多维数据集折叠到地面。此方法已成功应用于室外环境中从移动机器人获取的3D激光扫描,以便构建用于导航的局部高程图。计算时间显示出相对于以前针对该问题的基于点的解决方案有所改进。

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