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Robot mapping in large-scale mixed indoor and outdoor environments

机译:大型混合室内外环境中的机器人映射

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Tactical situational awareness in unstructured and mixed indoor/ outdoor scenarios is needed for urban combat as well as rescue operations. Two of the key functionalities needed by robot systems to function in an unknown environment are the ability to build a map of the environment and to determine its position within that map. In this paper, we present a strategy to build dense maps and to automatically close loops from 3D point clouds; this has been integrated into a mapping system dubbed OmniMapper. We will present both the underlying system, and experimental results from a variety of environments such as office buildings, at military training facilities and in large scale mixed indoor and outdoor environments.
机译:在城市战斗以及救援行动中,需要在非结构化和室内/室外混合场景中的战术态势感知能力。机器人系统在未知环境中运行所需的两个关键功能是建立环境图并确定其在该图中的位置的能力。在本文中,我们提出一种策略来构建密集的地图并自动关闭3D点云的循环。它已集成到名为OmniMapper的映射系统中。我们将展示底层系统以及各种环境的实验结果,这些环境包括办公楼,军事训练设施以及大规模混合的室内和室外环境。

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