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Controlling Minimally-Actuated Vehicles for Applications in Ocean Observation

Smith, Ryan N. & Huynh, Van T. (2012) Controlling Minimally-Actuated Vehicles for Applications in Ocean Observation. In Controlling minimally-actuated vehicles for applications in ocean observation, Elservier, Porto, Portugal, pp. 31-36.

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Abstract

Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.

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ID Code: 49819
Item Type: Conference Paper
Additional URLs:
Keywords: Profiling float, Lagrangian motion, Ocean model, minimal actuation
DOI: 10.3182/20120410-3-PT-4028.00007
ISBN: 978-3-902823-19-9
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > APPLIED MATHEMATICS (010200) > Dynamical Systems in Applications (010204)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > MARITIME ENGINEERING (091100) > Special Vehicles (091106)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 24 Apr 2012 10:27
Last Modified: 14 Mar 2013 22:28

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