Robot assisted analysis of suspicious objects in public spaces using CBRN sensors in combination with high-resolution LIDAR

This paper presents our approach for a remotely operated robot-based system to perform analysis tasks of suspicious objects such as luggage, trash cans, and similar items with regards to potential terroristic attacks using C(B)R(N)E (chemical, biological, radioactive, nuclear and explosive) substances in public spaces. To reduce the exposure risk for security forces, an existing robot-based system was equipped with a range of sensors including a high-resolution 3D-RGB scanner, gamma and chemical sensors, additional cameras, and positioning sensors. A flexible and modular sensor framework has been designed and implemented that supports efficient integration of multiple sensors of different kinds. The sensor framework is easily extendable and independent of the sensors, so that new components can be integrated with little effort. Data of all sensors is securely transferred to a base processing unit for fusion and processing. A high-resolution 3D model of the surroundings is enriched by the acquired data of all sensors and visualized to improve the situational awareness during mission operation by better perception of the remote situation