Simultaneous Tracking and Sampling of Dynamic Oceanographic Features with AUVs and Drifters

We present AUV survey methodologies to track and sample an advecting patch of water. Current AUV-based sampling rely primarily on geographic waypoint track-line surveys that are suitable for static or slowly changing features. When studying dynamic, rapidly evolving oceanographic features, such methods at best introduce error through insufficient spatial and temporal resolution, and at worst completely miss the spatial and temporal domain of interest. In this work, we extend existing oceanographic sampling methodologies to perform Lagrangian observation studies to sample within the context of an advecting feature of interest. We use GPS-tracked Lagrangian drifters to tag a patch of interest, and utilize its periodic position updates to make an AUV perform surveys around it as it gets advected by ocean currents. Two approaches are described and tested in two field trials in 2010 a one day experiment in June, followed by a five-day offshore experiment in September. Results from the experiments are presented along with the analysis of the sources of error.

[1]  Stephen M. Rock,et al.  Sonar-based iceberg-relative navigation for autonomous underwater vehicles , 2011 .

[2]  Naomi Ehrich Leonard,et al.  Control of coordinated patterns for ocean sampling , 2007, Int. J. Control.

[3]  Christopher Kitts,et al.  Entrapment/escorting and patrolling missions in multi-robot cluster space control , 2009, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  David M. Fratantoni,et al.  Multi-AUV Control and Adaptive Sampling in Monterey Bay , 2006, IEEE Journal of Oceanic Engineering.

[5]  Frederic Py,et al.  Adaptive Control for Autonomous Underwater Vehicles , 2008, AAAI.

[6]  Eric W. Frew,et al.  Cooperative Stand-off Tracking of Moving Targets by a Team of Autonomous Aircraft , 2005 .

[7]  Frederic Py,et al.  A deliberative architecture for AUV control , 2008, 2008 IEEE International Conference on Robotics and Automation.

[8]  R. Lumpkin,et al.  Measuring surface currents with Surface Velocity Program drifters : the instrument , its data , and some recent results , 2022 .

[9]  Russ E. Davis,et al.  LAGRANGIAN OCEAN STUDIES , 1991 .

[10]  Bruno Siciliano,et al.  Modelling and Control of Robot Manipulators , 1997, Advanced Textbooks in Control and Signal Processing.

[11]  Gaurav S. Sukhatme,et al.  Landing on a Moving Target Using an Autonomous Helicopter , 2003, FSR.

[12]  P. Bhatta,et al.  Multi-AUV control and adaptive sampling in Monterey Bay , 2004, 2004 IEEE/OES Autonomous Underwater Vehicles (IEEE Cat. No.04CH37578).

[13]  Frederic Py,et al.  A systematic agent framework for situated autonomous systems , 2010, AAMAS.

[14]  R. Lumpkin,et al.  Lagrangian Analysis and Prediction of Coastal and Ocean Dynamics: Measuring surface currents with Surface Velocity Program drifters: the instrument, its data, and some recent results , 2007 .

[15]  Gaurav S. Sukhatme,et al.  Autonomous Underwater Vehicle trajectory design coupled with predictive ocean models: A case study , 2010, 2010 IEEE International Conference on Robotics and Automation.

[16]  A Franchi,et al.  Distributed target localization and encircling with a multi-robot system , 2011 .

[17]  Andrea Doglioli,et al.  Study of a mesoscale anticyclonic eddy in the western part of the Gulf of Lion. , 2011 .