Collective Motion, Sensor Networks, and Ocean Sampling The goal is design and control of optimum trajectories for mobile sensor networks, like a fleet of self-directed underwater gliders that move with ocean currents and sample dynamic ocean variables.

This paper addresses the design of mobile sensor networks for optimal data collection. The development is strongly motivated by the application to adaptive ocean sampling for an autonomous ocean observing and prediction system. A performance metric, used to derive optimal paths for the network of mobile sensors, defines the optimal data set as one which minimizes error in a model estimate of the sampled field. Feedback control laws are presented that stably coordi- nate sensors on structured tracks that have been optimized over a minimal set of parameters. Optimal, closed-loop solu- tions are computed in a number of low-dimensional cases to illustrate the methodology. Robustness of the performance to the influence of a steady flow field on relatively slow-moving mobile sensors is also explored.

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