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MENTOR - Machine-learning based control of complex multi-agent systems
for search and rescue operations in natural disasters

WP4 - Application to Search and Rescue operations in natural disasters

This WP will be focussed on exploiting the results of WP3 for engineering multi-agent autonomous systems able to be deployed for SAR applications in natural disaster zones. Given the time scale of the project, we will study a variety of emergency scenarios using simulations. We will develop environments for simulations and also visualization using tools like Unity. These simulations will be data-driven involving experts from civil protection and emergency services. In particular, we will consider scenarios where there are constraints given by the nature of the disaster (e.g., volcanic eruptions, earthquakes, and environmental disasters), morphology of the territory and availability of rescue crews. Units at NA and BO will also benefit from collaborations with groups at Sydney and New York for the numerical and experimental investigation of the proposed solutions. We believe that the results of the experiments will provide a powerful proof-of-concepts for these technologies and demonstrate their general applicability for future potential adoption and deployments, not only for SAR.