3-D Effects, Robustness and Model Validation Issues in Drifter Motion Planning for Optimal Surveillance of the Ocean (DRIMPOS)
STATEN ISLAND COLL NY
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In recent years substantial progress, much of it resulting directly from ONR funding initiatives, has been made in understanding fundamental features of transport and mixing in oceans using methods derived from dynamical systems theory. The purpose of the current collaborative research is to extend these methods to the design of control algorithms for Drifter Motion Planning for Optimal Surveillance of the Ocean DRIMPOS. This effort is a direct attempt to transition Lagrangian based dynamical systems methods from diagnostic, postdictive tools to essential and active components in the design of oceanographic and naval observing systems. The specific goals of the research project include the development of flow-based control algorithms for drifting autonomous sensing systems. Couple dynamical systems ideas and control-theoretic algorithms to produce real-time control of gliders based on the output from high resolution coastal ocean model forecasting systems. Specifically, use knowledge of Lagrangian ocean dynamics to develop readily computable, optimal control algorithms to 1 maximize the loitering time of autonomous surveillance platforms in a prescribed region under energy constraints 2 minimize the distance, over an extended time period, between a platform and a specified location in the flow 3 optimize sensor coverage of a given surveillance region by single or multiple platforms and 4 perform optimal path planning for an AUV platform by minimizing time to reach any number of specified way-points along a desired observational route.
- Physical and Dynamic Oceanography