Real-Time Probabilistic Reachability Forecasting for Gliders in the Gulf of Mexico

As part of the Mini-Adaptive Sampling Test Run (MASTR) experiment in the Gulf of Mexico (GoM) region from February to April 2024, we demonstrated real-time deterministic and probabilistic reachability analysis and time-optimal path planning to guide a fleet of four ocean gliders. The governing differential equations for reachability analysis and time-optimal path planning were numerically integrated in real-time and forced by currents from our large-ensemble ocean forecasts. We illustrate the real-time deterministic and probabilistic forward reachability analyses, reachability and path planning for glider pickups, time-optimal path planning for gliders in distress, and planning of future glider deployments. Results show that the actual paths of gliders were contained within our reachable set forecasts and in accord with the dynamic reachability fronts. Our time-optimal headings and paths also predicted real glider motions, even for longer-range predictions of weeks to a month duration. Reachability and time-optimal path planning forecasts were successfully employed for glider recovery. They also enabled exploring options for future glider deployments.

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Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/oceans55160.2024.10754057
Citations
3
Primary Topic
Maritime Navigation and Safety
Type
article
Field-Weighted Citation Impact
1.01
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article

Real-Time Probabilistic Reachability Forecasting for Gliders in the Gulf of Mexico

Lynn K. Shay, Yina Liu, Uchenna C. Nwankwo, Sheila Glenn et al.
3 citations
Maritime Navigation and Safety
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article

Real-Time Probabilistic Reachability Forecasting for Gliders in the Gulf of Mexico

Lynn K. Shay, Yina Liu, Uchenna C. Nwankwo, Sheila Glenn, Julie L. Marble, Heather Furey, Anthony H. Knap, Graham Stuart, Chris Mirabito, Patrick J. Haley, K. Coleman, Benjamín Jaimes, Julio Sheinbaum, Jan van Smirren, Steven F. DiMarco, Eric P. Chassignet, P. Barros, David Alberto Salas‐de‐León, Suhail Mahmud, E. M. Mule, Jill Storie, Pierre F. J. Lermusiaux, Víctor Kevin Contreras Tereza, Marc Feldman, Michael Leber, Travis Miles, Amy S. Bower, Paula Pérez‐Brunius, Rosalinda Monreal Jiménez, Miguel Tenreiro, X. Ge, Roberto Ramos, Michael Smith, David Aragon, Dirk G. Wilson, M. Khadka, A. Dancer
article en
3 citations

Abstract

As part of the Mini-Adaptive Sampling Test Run (MASTR) experiment in the Gulf of Mexico (GoM) region from February to April 2024, we demonstrated real-time deterministic and probabilistic reachability analysis and time-optimal path planning to guide a fleet of four ocean gliders. The governing differential equations for reachability analysis and time-optimal path planning were numerically integrated in real-time and forced by currents from our large-ensemble ocean forecasts. We illustrate the real-time deterministic and probabilistic forward reachability analyses, reachability and path planning for glider pickups, time-optimal path planning for gliders in distress, and planning of future glider deployments. Results show that the actual paths of gliders were contained within our reachable set forecasts and in accord with the dynamic reachability fronts. Our time-optimal headings and paths also predicted real glider motions, even for longer-range predictions of weeks to a month duration. Reachability and time-optimal path planning forecasts were successfully employed for glider recovery. They also enabled exploring options for future glider deployments.

Rutgers, The State University of New Jersey (US), Florida State University (US), Woodwell Climate Research Center (US), University of Miami (US), University of the Virgin Islands (VI), National Academies of Sciences, Engineering, and Medicine (US), Fugro (Norway) (NO), Rutgers Sexual and Reproductive Health and Rights (NL), Massachusetts Institute of Technology (US), Centro de Investigación Científica y de Educación Superior de Ensenada (MX), Woods Hole Oceanographic Institution (US), Universidad Nacional Autónoma de México (MX), Texas A&M University (US)
Climate action
Openalex Percentile: Top 24%
Maritime Navigation and Safety
1.01
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