Collective Motion, Sensor Networks and Ocean Sampling
Naomi Ehrich Leonard, Derek Paley, Francois Lekien, Rodolphe Sepulchre, David M. Fratantoni and Russ Davis
Accepted for publication in Proceedings of the IEEE,
Special Issue on Networked Control Systems, 2006.
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 coordinate sensors on structured
tracks that have been optimized over a minimal set of parameters.
Optimal, closed-loop solutions 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.