Exploring scalar fields using multiple sensor platforms: Tracking level curves

Fumin Zhang, Edward Fiorelli, Naomi Ehrich Leonard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

53 Scopus citations

Abstract

Autonomous mobile sensor networks are employed to measure large scale environmental scalar fields. Yet an optimal strategy for mission design addressing both the cooperative motion control and the collaborative sensing is still under investigation. We develop one strategy which uses four moving sensor platforms to explore a noisy scalar field defined in the plane; each platform can only take one measurement at a time. We derive a Kalman filter in conjunction with a nonlinear filter to produce estimates for the field value, the gradient and the Hessian along the averaged trajectories of the moving platforms. The shape of the platform formation is designed to minimize error in the estimates, and a cooperative control law is designed to asymptotically achieve the optimal formation. We develop a motion control law to allow the center of the platform formation to move along level curves of the averaged field. Convergence of the control laws are proved, and performance of both the filters and the control laws are demonstrated in simulated ocean fields.

Original languageEnglish (US)
Title of host publicationProceedings of the 46th IEEE Conference on Decision and Control 2007, CDC
Pages3579-3584
Number of pages6
DOIs
StatePublished - 2007
Event46th IEEE Conference on Decision and Control 2007, CDC - New Orleans, LA, United States
Duration: Dec 12 2007Dec 14 2007

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other46th IEEE Conference on Decision and Control 2007, CDC
CountryUnited States
CityNew Orleans, LA
Period12/12/0712/14/07

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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