BRITE Relaunch: Persistent and Accessible Maritime Monitoring (PAMM)

George Mason University, Fairfax VA

Investigators

Abstract

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This Boosting Research Ideas for Transformative and Equitable Advances in Engineering (BRITE) Relaunch project represents a unified research and education program dedicated to creating opportunities for students interested in, and researchers requiring, persistent and accessible maritime monitoring. With a blended program of STEM outreach for students in grades 6-12 to promote interest in maritime robotics, undergraduate project-based learning in the design and construction of novel marine vehicles, and graduate level research on the use of accessible control hardware coupled with machine learning to support coordinated control of multi-vehicle maritime robotics operations, these efforts will develop tools, platforms, and a workforce that will improve the applications of unmanned marine vehicles and expand opportunities for their use to support research in a variety of maritime environments. The novel control systems that will be developed through this project will inform other unmanned vehicle operation. By integrating control input systems that are often used by individuals with significant limitations in motion (e.g., eye gaze and sip-and-puff), this project will also open up data collection in maritime environments to a broader population, including those with disabilities.. The researched Persistent and Accessible Maritime Monitoring (PAMM) activities further the state of the art of maritime robotics through novel vehicle design and innovative use of machine learning to support multi-vessel coordinated control while reducing physical demands associated with marine robotics use. Vehicle design activities will be focused on systems that will enable data gathering: (1) in coastal and riverine environments before, during, and after a storm; (2) over extended durations where both efficiency and sprint capability to overcome current, waste water, or other heavy flows are required; and (3) in arctic climates where transitioning between ice and water may be critical for environmental monitoring. Machine learning supported, human-in-the-loop, marine vehicle control using controllers more commonly seen in the accessibility community, such as sip-and-puff and eye gaze control, will reduce barriers for researchers with physical constraints while also providing new opportunities for all scientists using maritime robotics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.