Collaborative Research: Ideas Lab: ETAUS Meshed Observations of THE Remote Subsurface with Heterogeneous Intelligent Platforms (MOTHERSHIP)

About This Grant

Melting of ice shelves by warm ocean waters destabilizes glaciers, enhancing ice flow into the ocean and contributing to global sea level rise. Measurements of ocean properties under ice shelves are needed to improve global predictions of sea level rise and to anticipate its societal consequences. Such measurements, however, are challenging to obtain. In this Ideas Lab: Engineering Technologies to Advance Underwater Sciences (ETAUS) project, a proof-of-concept mothership-and-passenger system will be developed to permit the future deployment of a highly capable, autonomous underwater vehicle (the mothership), programmed to travel as far as safely possible under ice shelves to release a swarm of novel, low-cost passenger robots that will coordinate to explore further into the ice cavity. The hardware prototypes, networked communication systems and protocols, and coordination algorithms developed as part of this project’s mothership-and-passenger system will help advance the field of underwater exploration in confined and hard-to-reach environments. The project will also foster the training of future scientists and engineers by engaging youths from small fishing communities in Oregon through presentations at Oregon’s MATE ROV Regional Competition, by employing high-school interns through the Apprenticeships in Science and Engineering (ASE) Summer Academy Program, and by training multiple undergraduate and graduate students at participating institutions. The goal of this project is to develop a mothership-and-passenger sampling system to reach difficult-to-access glacier grounding zones via the open ocean to measure the extent of ice cavities and surrounding water properties. The project will innovate along three main areas of inquiry: 1) passenger robot design, 2) acoustic communication protocols and hardware, and 3) mothership-and-passenger coordination algorithms. Novel, low-cost passenger robots will be conceived that can switch through different operation modes to optimize maneuverability, power consumption, or a combination of both, as needed for various tasks throughout a deployment. Acoustic communication protocols and hardware will be developed to prioritize robust communication between passenger robots over throughput and permit swarm self-localization by utilizing time-of-flight and angle-of-arrival between passengers to estimate relative positions. Swarm coordination algorithms will be designed to estimate flow direction and strength from the passenger robots’ relative positions to optimize navigation and power consumption. The performance of the network will be tested in increasingly challenging environments, i.e., tests will be conducted in a pool, an unfrozen lake, and finally in a frozen lake, while network capabilities with a larger swarm will be modeled to ensure the scalability of the system to ocean deployments. Finally, the software developed for the mothership-and-passenger communication and self-localization protocols will be generalizable and made available open-source to allow other research teams to adapt the system to their own needs. The mothership-and-passenger sampling system will not only advance under-ice-observation capabilities but also have wider oceanographic applications such as detection and monitoring of underwater harmful algal blooms or anoxic events threatening fisheries. 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.