Collective motion, sensor networks, and ocean sampling

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

Research output: Contribution to journalArticlepeer-review

725 Scopus citations

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

Original languageEnglish (US)
Article number4118466
Pages (from-to)48-74
Number of pages27
JournalProceedings of the IEEE
Volume95
Issue number1
DOIs
StatePublished - Jan 2007

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Electrical and Electronic Engineering

Keywords

  • Adaptive sampling
  • Autonomous underwater vehicles
  • Cooperative control
  • Coordinated dynamics
  • Mobile sensor networks
  • Ocean sampling
  • Underwater gliders

Fingerprint

Dive into the research topics of 'Collective motion, sensor networks, and ocean sampling'. Together they form a unique fingerprint.

Cite this