FRIDI: First Responder Interface for Disaster Information

In recent years robots have been deployed in numerous occasions to support disaster mitigation missions through exploration of areas that are either unreachable or potentially dangerous for human rescuers. The UNR Robotics Research Lab has recently teamed up with a number of academic, industry, and public entities with the goal of developing an operator interface for controlling unmanned autonomous system, including the UAV platforms to enhance the situational awareness, response time, and other operational capabilities of first responders during a disaster remediation mission. The First Responder Interface for Disaster Information (FRIDI) will include a computer-based interface for the ground control station (GCS) as well as the companion interface for portable devices such as tablets and cellular phones. Our user interface (UI) is designed with the goal of addressing the human-robot interaction challenges specific to law enforcement and emergency response operations, such as situational awareness and cognitive overload of the human operators.

Situational Awareness, or otherwise the understanding that the human operator has about the location, activities, surroundings, and the status of the unmanned aerial vehicle (UAV), is a key factor that determines the success in a robot-assisted disaster mitigation operation. With that in mind, our goal is to design an interface that will use pre-loaded terrain data augmented with real-time data from the UAV sensors to provide for a better SA during the disaster mitigation mission. Our UI displays a map of near-live images of the scene as recorded from UAVs, position and orientation of the vehicles in the map, as well as video and other sensor readings that are crucial for the efficiency of the emergency response operation. This UI layout enables human operators to view and task multiple individual robots while also maintaining full situational awareness over the disaster area as a whole.



  • Ahmed Siddiqui, K., Feil-Seifer, D., Yang, T., Jose, S., Liu, S., & Louis, S. Development of a Swarm UAV Simulator Integrating Realistic Motion Control Models For Disaster Operations. In Proceedings of the ASME Dynamic Systems and Controls Conference (DSCC), page V003T39A003, Tysons Corner, Virginia, Oct 2017. ( details ) ( .pdf )
  • Pham, X. H., La, H., Feil-Seifer, D., & Deans, M. A Distributed Control Framework of Multiple Unmanned Aerial Vehicles for Dynamic Wildfire Tracking. In IEEE Transactions on Systems, Man and Cybernetics: Systems, Apr 2018. ( details )
  • Blankenburg, J., Banisetty, S., Hoseini, S., Fraser, L., Feil-Seifer, D., Nicolescu, M., & Nicolescu, M. A Distributed Control Architecture for Collaborative Multi-Robot Task Allocation. In International Conference on Humanoid Robots, Birmingham, UK, Nov 2017. ( details ) ( .pdf )