UGV-CBRN：用于化学、生物、放射性和核灾害响应的无人地面车辆
UGV-CBRN: An Unmanned Ground Vehicle for Chemical, Biological, Radiological, and Nuclear Disaster Response
AI总结：
针对CBRN灾害，提出UGV-CBRN无人地面车辆，集成自主辐射测绘、半自主采样与在线分析，通过移动机械手和拉曼光谱仪实现远程威胁定位与评估，并在EnRicH挑战中验证。
摘要：
机器人搜索与救援（SAR）通过加速灾害评估并使操作员远离危险环境来支持响应团队。在发生化学、生物、放射性和核（CBRN）灾害时，机器人被部署以识别和定位辐射源。随后，人类响应者评估情况并消除危险。所提出的系统朝着增强机器人融入SAR团队的方向迈出了一步。将自主辐射测绘与半自主物质采样以及CBRN威胁的在线分析相结合，使人类操作员能够从安全距离定位和评估威胁。使用两个激光雷达、一个惯性测量单元（IMU）和一个盖革计数器来测绘周围区域并定位潜在的辐射源。一个具有六个自由度的移动机械手操纵阀门并采样物质，这些物质由车载拉曼光谱仪进行分析。人类操作员从远程位置监控任务的进展，定义目标位置并指导半自主操纵过程。多样的恢复行为有助于机器人部署、系统状态监控以及硬件和软件的恢复。现场测试展示了所提出系统在欧洲机器人黑客马拉松（EnRicH）的CBRN灾害响应挑战试验中的能力。我们通过GitHub仓库提供记录的传感器数据和实现的软件：https://github.com/TW-Robotics/search-and-rescue-robot-2024。
英文摘要：
Robotic search and rescue (SAR) supports response teams by accelerating disaster assessment and by keeping operators away from hazardous environments. In the event of a chemical, biological, radiological, and nuclear (CBRN) disaster, robots are deployed to identify and locate radiation sources. Human responders then assess the situation and neutralize the danger. The presented system takes a step toward enhanced integration of robots into SAR teams. Integrating autonomous radiation mapping with semi-autonomous substance sampling and online analysis of the CBRN threat lets the human operator localize and assess the threat from a safe distance. Two LiDARs, an IMU, and a Geiger counter are used for mapping the surrounding area and localizing potential radiation sources. A mobile manipulator with six Degrees of Freedom manipulates valves and samples substances that are analyzed by an onboard Raman spectrometer. The human operator monitors the mission's progression from a remote location defining target locations and directing the semi-autonomous manipulation processes. Diverse recovery behaviours aid robot deployment, system state monitoring, as well as recovery of hard- and software. Field tests showcase the capabilities of the presented system during trials at the CBRN disaster response challenge European Robotics Hackathon (EnRicH). We provide recorded sensor data and implemented software through a GitHub repository: https://github.com/TW-Robotics/search-and-rescue-robot-2024.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
