数字化CBRNE应急响应场景的多模态扫描系统

M. Salathe, B. Quiter, M. Bandstra, Xin Chen, V. Negut, Micah Folsom, G. Weber, Christopher Greulich, M. Swinney, N. Prins, D. Archer
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引用次数: 1

摘要

描述了一种手持式系统,用于数字化对化学、生物、放射性、核和/或爆炸物(CBRNE)事件现场的上下文理解。该系统使用激光雷达和摄像头来创建环境的彩色3D模型,这有助于在现场支持响应的领域专家。为了生成数字化模型,响应者通过携带系统在现场扫描任何可疑物体和周围环境。扫描系统提供实时用户界面,告知用户扫描进度,并指出激光雷达传感器或摄像头可能错过的任何区域。目前,收集到的数据在不同的设备上进行后处理,建立遇到场景的彩色三角形网格,意图在稍后将该管道移动到扫描仪上。网格被充分压缩,可以通过减少的带宽连接发送给远程分析人员。此外,该系统还可以跟踪附着在可疑物体周围的诊断设备上的基准标记。由此产生的跟踪信息可以传送给远程分析人员,以进一步促进他们的支持工作。本文将讨论系统的设计、软件组成、用于扫描场景的用户界面、传感器校准的必要程序以及结果数据的处理步骤。讨论将以评估系统在11个场景中的性能结束。
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A multi-modal scanning system to digitize CBRNE emergency response scenes
A handheld system developed to digitize a contextual understanding of the scene at a chemical, biological, radiological, nuclear and/or explosives (CBRNE) events is described. The system uses LiDAR and cameras to create a colorized 3D model of the environment, which helps domain experts that are supporting responders in the field. To generate the digitized model, a responder scans any suspicious objects and the surroundings by carrying the system through the scene. The scanning system provides a real-time user interface to inform the user about scanning progress and to indicate any areas that may have been missed either by the LiDAR sensors or the cameras. Currently, the collected data are post-processed on a different device, building a colorized triangular mesh of the encountered scene, with the intention of moving this pipeline to the scanner at a later point. The mesh is sufficiently compressed to be sent over a reduced bandwidth connection to a remote analyst. Furthermore, the system tracks fiducial markers attached to diagnostic equipment that is placed around the suspicious object. The resulting tracking information can be transmitted to remote analysts to further facilitate their supporting efforts. The paper will discuss the system's design, software components, the user interface used for scanning a scene, the necessary procedures for calibration of the sensors, and the processing steps of the resulting data. The discussion will close by evaluating the system's performance on 11 scenes.
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