Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions
Data(s) |
01/05/2010
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Resumo |
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 plat- forms. 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. |
Formato |
application/pdf |
Identificador | |
Relação |
http://eprints.qut.edu.au/40122/1/655.pdf http://cres.usc.edu/cgi-bin/printpubdetails.pl?pubid=655 Smith, Ryan N. , Das, Jnaneshwar, Chao, Yi, Caron, David A., Jones, Burton H., & Sukhatme, Gaurav S. (2010) Cooperative multi-AUV tracking of phytoplankton blooms based on ocean model predictions. In Proceedings of Oceans '10 - IEEE Sydney, Sydney, Australia, pp. 1-10. |
Direitos |
Copyright 2010 (please consult the authors). |
Fonte |
Faculty of Built Environment and Engineering; School of Engineering Systems |
Palavras-Chave | #040501 Biological Oceanography #040503 Physical Oceanography #080101 Adaptive Agents and Intelligent Robotics #091103 Ocean Engineering #Autonomous Underwater Vehicle #Algal bloom #Ocean modeling #Path Planning #Multi-vehicle control |
Tipo |
Conference Paper |