Ricerc@Sapienza

Preparedness and response of urban actors to different emergencies are among the main goals of several EU calls. A major issue occurring when rescuers leave for an emergency is the limited knowledge about the gravity of the problem. Also the intervention may not be immediate due to the physical distance of the rescue team from the emergency point or its commitment in a previous request. Providing situational awareness is widely recognized as an invaluable tool because it allows the rescue team to "see" what happens on the spot before intervening, properly planning the rescue mission.

This project aims at designing an autonomous and multipurpose squad of Unmanned Aerial Vehicles (UAVs), or drones, that can explore the area before the rescuers intervention and provide a view of the situation. The squad can be deployed on demand, offering a variety of first-response services (e.g., locating people who need help, making them communicate with the depot, picking up and delivering necessities). This is a challenging issue due to the potential vastness of the area: it is not possible to remotely control drones that are often disconnected from the depot.

Our project aims to be of aid to the human in the control loop, by making drone squads autonomous, self-configuring, and able to predict the type of required intervention. Our project will develop intelligent algorithms and predictive models that allow the UAVs squad to coordinate and take decisions on mission and trajectory planning, data routing, item delivery, and rescue prediction in a secure way. The research involved in this project is highly interdisciplinary, as it includes networking and management, machine learning, and blockchain aspects. We expect to revolutionize rescue operations supporting rescuers with a pre-mission view, to offer remote assistance (before being able to physically intervene) and plan an appropriate intervention. We believe this system will help save more lives.