This collaborative project addresses the need for ocean observational techniques which was highlighted by the recent Deepwater Horizon incident. The proposed project investigates heterogeneous ocean robots (including wave gliders, unmanned surface vessels, and autonomous underwater vehicles) to detect and monitor the propagation of oil plumes. Specific objectives include: 1) the development of a distributed multi-robot cooperative deployment algorithm using partial differential equation (PDE) based methods that match the oceanographic model of oil transport, 2) the development of authentic dynamic model of the new wave glider platform to incorporate in the cooperative control, and 3) assessing the potential advantages of innovative algorithms through simulations and experimental demonstration in a coastal experiment using a network of ocean robot platforms.
Broader Impacts: The proposed project will provide novel algorithmic and software support for collective sensing, and address a pressing real-world need for better sensing of underwater hydrocarbon plumes. The techniques developed in the proposal will have long-term impacts in underwater exploration such as oceanographic survey and energy production in deep water. The results may also potentially benefit other environmental monitoring tasks with underlying diffusion and advection processes, such as weather event tracking and climate prediction. The planned work will integrate research projects with education activities through robot-centric undergraduate and graduate education, robotics competition, short course and workshop development, and outreach to K-12 education. Partnering with the Stevens' Center for Innovation in Engineering and Science Education, the project will showcase the proposed research in the curriculum of the Stevens Build IT Underwater Robotics Scale-Up for STEM Learning and Workforce Development Project awarded by NSF.
