headgraphic
loader graphic

Loading content ...

Northern Arabian Sea Circulation - autonomous research:

Optimal Planning Systems (NASCar-OPS)

P.F.J. Lermusiaux, P.J. Haley, Jr.,
C. Mirabito, C. Kulkarni, D. Subramani, S. Jana

Massachusetts Institute of Technology
Ocean Science and Engineering
Mechanical Engineering
Cambridge, Massachusetts

Project Summary
Real-time Sea Exercises
Ongoing MIT-MSEAS Research
Additional NASCar-OPS Links
Background Information
References

 

salinity.png floats.png
This research is sponsored by the Office of Naval Research.

Project Summary

Today, the number of autonomous platforms used in semi-coordinated sea operations can be larger than 10 and this number is increasing. This new paradigm in ocean science and operations calls for investigations as those envisioned by the Northern Arabian Sea Circulation – autonomous research (NASCar) initiative. The need for clever autonomous observing and prediction systems is especially acute in the NASCar region due to the frequent pirate activities and the relative paucity of in situ observations.

Background information is available below.

Top of page

Real-time Sea Exercises

NASCar-OPS Sea Exercise 2017. The real-time exercise occurs in the Arabian Sea during February-March 2017. In collaboration with the NASCar team, we utilize our multi-resolution MSEAS PE modeling system to: (i) forecast the regional high-resolution ocean fields and their probability; (ii) utilize these fields to forecast the reachability sets and fronts of underwater vehicles; (iii) forecast the uncertainty of such reachability fields and optimal paths.

Real-time modeling products and data sources can be found on the Sea Exercises page.

  vorticity.png
Top of page

Ongoing MIT-MSEAS Research

Long-Term Goals:

  1. Apply our theory and schemes for rigorous optimal path planning and persistent ocean sampling with swarms of autonomous vehicles, and
  2. Further quantify the dynamics and variability of the circulation features and mixed layer, and the responses to monsoon winds, utilizing multi-resolution data-assimilative ocean modeling and process studies.

Objectives:

Presentations and Meetings

NASCar-OPS-supported Publications

Top of page

Additional NASCar-OPS Links

Links from ONR Arabian Sea (NASCar) Interior Working Group

Top of page

Background Information

One of our motivations is to apply the theory and schemes we derived for optimal path planning of swarms of ocean vehicles operating for long-duration in strong and dynamic currents (Lolla et al, 2012a, b; Lolla et al, 2014a,b; Lermusiaux et al., 2015; Lolla and Lermusiaux, 2015). For any given ocean currents (however strong), our level-set equations provide the exact time-optimal paths to travel from one location to another. The methodology has been extended to energy-optimal (Subramani et al., 2015) and swarm-optimal (Lolla et al., 2015) paths. It can also account for uncertainty (Lermusiaux et al., 2015), predicting the probability density functions of optimal path fields. Finally, we plan to provide guidance for the optimal sampling of the region (e.g. Lermusiaux, 2007). This includes Observation System Simulation Experiments (OSSEs).

The other motivation is to further the understanding of the dynamics in the region, focusing on the variability in time and space of the circulation features and of the mixed-layer, and on the responses of this dynamics to forcing by monsoon winds. Our interests include the dynamics of the wind-driven and buoyancy-driven currents and eddies, especially in relation to the mixed-layer physics and the western boundary currents. These features need to be further described and characterized, and their interactions need to be better understood and quantified. The NASCar DRI is well positioned to make major contributions to this understanding. Both our optimal path planning and quantitative dynamics research activities will be enabled by our multi-resolution ocean modeling of the region. Process-based modeling is also critical and will be utilized.

Our research questions relate to:

Specific Research Tasks

Optimal Path Planning of Swarms of Autonomous Vehicles for Persistent Sampling

Quantitative Dynamics Analyses using Process-oriented and Multi-resolution Modeling

Top of page

References

Top of page

Go to the MSEAS home page