Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions

Ryan N. Smith, Jnaneshwar Das, Chao Yi, David A. Caron, Burton H. Jones, Gaurav S. Sukhatme

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

13 Scopus citations


In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor platforms. Currently, most AUV deployments execute a lawnmower-type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.

Original languageEnglish (US)
Title of host publicationOCEANS'10 IEEE Sydney, OCEANSSYD 2010
StatePublished - 2010
Externally publishedYes
EventOCEANS'10 IEEE Sydney, OCEANSSYD 2010 - Sydney, NSW, Australia
Duration: May 24 2010May 27 2010

Publication series



OtherOCEANS'10 IEEE Sydney, OCEANSSYD 2010
CitySydney, NSW

ASJC Scopus subject areas

  • Ocean Engineering


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