NRI: Coordinated Detection and Tracking of Hazardous Agents with Aerial and Aquatic Robots to Inform Emergency Responders

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New tools and technology are needed to rapidly assess hazardous agents in the environment and inform emergency responders. Unmanned surface vehicles (USVs) have been used to monitor pollutant plumes in aquatic environments. However, USVs can only provide a close-up view of the plumes. Unmanned aerial systems (UASs) can survey large areas, but only from a distance. This project addresses the challenges in tracking flows of pollutants using a team of UASs and USVs. UASs are used as scouts to direct USVs to efficiently sample the water for testing. The results will provide emergency responders with technology that can provide rapid, actionable information on the dispersal of hazardous agents. This technology will be of immediate value in the development of early-warning systems for airborne hazards such as chemicals and radioactive particles. In an effort to encourage careers in robotics and emergency response, this project delivers a unique interdisciplinary robotics unit for 75 high school students. Efficient coordination algorithms are required to fully exploit heterogeneity in sensing of teams of autonomous surface and aerial vehicles. When moving through the water, a plume of hazardous agents may bifurcate into different flow regimes, complicating the sampling and control scenario. This project: (1) develops approximation algorithms for multi-resolution, informative trajectory planning to track spatio-temporal plumes with UAS teams; (2) develops an autonomous USV to sample and characterize a surrogate hazardous agent in the water and air; (3) conducts field sampling campaigns with emergency responders (Virginia Tech Rescue Squad, a unique group of stakeholders consisting of 50 student members) to find and localize sources of a surrogate hazardous agent; and (4) develops a unique interdisciplinary robotics unit for 75 high school students representing a range of ages, ethnicities, and socioeconomic classes.