Work

Collective Motion, Sensor Networks, and Ocean Sampling

Year: 2007

Type: article

Abstract: 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

Source: Proceedings of the IEEE

DOI: 10.1109/jproc.2006.887295

Authors: Naomi Ehrich Leonard, Derek A. Paley, Francois Lekien, Rodolphe Sepulchre, David M. Fratantoni, Russ E. Davis

Institutions: Princeton University, University of Liège, Woods Hole Oceanographic Institution, University of California San Diego

Language: English

Topic: Distributed Control Multi-Agent Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2025800439

FWCI: 99.66

Cites: 63

Cited by: 948

Related to: 9