一份报告称,在一个充满危险物质的工业大厅发生重大火灾后,空中机器人的部署

H. Surmann, Dominik Slomma, Stefan Grobelny, R. Grafe
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引用次数: 9

摘要

这份技术报告是关于在柏林发生重大火灾后对一个有危险物质的工业大厅进行侦察的任务和所获得的经验。在这次行动中,只使用了无人驾驶飞机和照相机来获取有关该地点和建筑物的信息。首先,为了规划进入大厅的入口,创建了建筑的地理参考3D模型。随后,无人机被用来在严重受损的内部飞行,并从大厅内部拍照。安装在无人机下的360°摄像机用于收集周围区域的图像,特别是从难以飞进的部分。由于收集到的数据集包含相似图像和模糊图像,因此使用视觉SLAM、束调整和模糊检测来清除非最优图像,从而计算出3D模型和概述。结果表明,紧急服务部门无法从3D模型中提取必要的信息。因此,我们实现了一个与其他360°图像链接的交互式全景查看器,其中与其他图像的链接依赖于视觉SLAM算法的半密集点云和定位相机位置,以便应急部队可以查看周围环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deployment of Aerial Robots after a major fire of an industrial hall with hazardous substances, a report
This technical report is about the mission and the experience gained during the reconnaissance of an industrial hall with hazardous substances after a major fire in Berlin. During this operation, only UAVs and cameras were used to obtain information about the site and the building. First, a geo-referenced 3D model of the building was created in order to plan the entry into the hall. Subsequently, the UAVs were used to fly in the heavily damaged interior and take pictures from inside of the hall. A 360° camera mounted under the UAV was used to collect images of the surrounding area especially from sections that were difficult to fly into. Since the collected data set contained similar images as well as blurred images, it was cleaned from non-optimal images using visual SLAM, bundle adjustment and blur detection so that a 3D model and overviews could be calculated. It was shown that the emergency services were not able to extract the necessary information from the 3D model. Therefore, an interactive panorama viewer with links to other 360° images was implemented where the links to the other images depends on the semi dense point cloud and located camera positions of the visual SLAM algorithm so that the emergency forces could view the surroundings.
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