CaltechPrincetonOffice of Naval Research
Mechanical and Aerospace Engineering
Dynamical Control Systems Laboratory
Princeton University
Princeton, NJ 08544
Princeton: Naomi Leonard, Clancy Rowley, Ralf Bachmayer, Josh Graver, Eddie Fiorelli, Pradeep Bhatta, Derek Paley.
Caltech: Jerry Marsden, Chad Coulliette, Francois Lekien, Shawn Shadden 
Monterey Bay '03 Experiment (August 3 - September 8, 2003)
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Real-Time Experimental Results

Proposed Plan for Adaptive Sampling Experiments in Monterey Bay '03 [doc]

Real-time Computations of Lagrangian Coherent Structures

Recent Publicity
New Jersey Public Television coverage on NJN News from 9/19/03. Use Real Player to watch. The story begins about 11 minutes into the program. Alternatively for higher quality, you can download an AVI file here , a zipped version can be found here. Copyright NJN News.
Recent Publications
Cooperative Control of Mobile Sensor Networks: Adaptive Gradient Climbing in a Distributed Environment
Submitted for publication
P. Ogren, E. Fiorelli and N.E. Leonard

Adaptive Sampling Using Feedback Control of an Autonomous Underwater Glider Fleet
Proc. 13th International Symposium on Unmanned Untethered Submersible Technology, E. Fiorelli, P. Bhatta, N.E. Leonard and I.Shulman.

Underwater Glider Model Parameter Identification
Proc. 13th International Symposium on Unmanned Untethered Submersible Technology, J.G. Graver, R. Bachmayer, N.E. Leonard and D.M. Fratantoni.

About AOSN II and Adaptive Sampling
AOSN-II is an ONR-sponsored, multi-institutional, collaborative research program with the central objective "to quantify the gain in predictive skill for principal circulation trajectories, transport at critical points and near-shore bioluminescence potential in Monterey Bay as a function of model-guided, remote adaptive sampling using a network of autonomous underwater vehicles". The overall goals of adaptive sampling are presented below; a most important purpose of adaptive sampling is to provide data for updating and evaluating forecast models.

In AOSN-II, the underwater vehicle network features a fleet of autonomous underwater gliders. Gliders are small, relatively simple and inexpensive, winged, buoyancy-driven submersibles that have high endurance and are strongly influenced by the currents. Adaptive sampling by the glider network should exploit these capabilities (e.g., by taking advantage of current forecasts to steer gliders efficiently) as well as the opportunity to use the glider network itself as a re-configurable, mobile sensor array.

MB'03, the first experiment in the AOSN-II program, is scheduled to take place in and around Monterey Bay in August 2003. There will be a number of data-collecting assets in addition to the glider network. For a description of the methods used to direct the glider fleet please see the adaptive sampling and forecasting plan [pdf], [doc]. The plan consists of five steps -

  1. Forecasting with HOPS-ESSE and ROMS.
  2. An integrated interpretation of the forecasts, forecast errors and dynamical hot spots (physical and/or coupled physical/biological).
  3. Analysis of the circulation fields by Lagrangian Coherent Structures (LCS).
  4. A collective decision by a Real Time Operations Committee (RTOC) as to what features and regions to be adaptively sampled the next day.
  5. Coordinated and cooperative control of the glider fleet using feedback.
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