UGV-CBRN: An Unmanned Ground Vehicle for Chemical, Biological, Radiological, and Nuclear Disaster Response

TL;DR

The paper addresses the need for integrated robotic systems in CBRN disaster response to minimize operator exposure while enabling rapid threat localization and containment. It presents UGV-CBRN, an unmanned ground vehicle that autonomously maps geometry and radiation fields, semi-autonomously samples substances, and analyzes samples online with a Raman spectrometer, all under human supervisory control. The approach leverages a ROS-based, Docker-contained software stack, 2D and 3D SLAM, Gaussian Process Regression for radiation mapping, and a multi-purpose end-effector for valve manipulation and sampling. Field trials at the EnRicH venue validate geometry and radiation mapping, substance sampling, and valve manipulation across indoor and outdoor scenarios, with a GitHub repository for software artifacts. The work advances SAR robotics by integrating CBRN sensing and manipulation into a single platform, enabling safer and faster disaster response.

Abstract

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.

Figures (8)

• Figure 1: UGV-CBRN A robotic system for assisting disaster response through geometry and radiation mapping, substance sampling and analysis, as well as valve manipulation.
• Figure 2: UGV-CBRN: Integrated system overview The proposed system aims to provide 2D and 3D mapping, radiation mapping, autonomous navigation and manipulation capabilities (blue rounded border) for sar missions. The figure depicts the data flow between functional units, sensors and the multi-purpose end-effector.
• Figure 3: Multi-purpose end-effector The left part of the figure shows a real image of the end-effector and the right part shows the schematics and integral components.
• Figure 4: UGV-CBRN: System operation The proposed system switches between autonomous navigation and operator input based on predetermined priorities. Manual input is always preferred over autonomous behavior.
• Figure 5: Autonomous Mapping results Visualized are the $3D$ geometry maps of all test scenarios. Color coding is used to indicate map height. In c), map fragmentation caused by challenging outdoor light is marked with black circles.