Adaptive sampling algorithms for rapidly mapping the outflow plume from a nuclear power plant are presented. Plume detection is based on the notion of a plume indicator function that, loosely speaking, indicates the likelihood that an environmental sample is from the plume rather than from the ambient environment. For the case of a power plant outflow, we show that a plume indicator function composed of several measured parameters, such as temperature, salinity, dissolved oxygen, and flow magnitude, greatly enhance the robustness of our adaptive sampling algorithms. Successful field trials using a small autonomous surface vehicle are reported. ©2006 IEEE.
CITATION STYLE
Cannell, C. J., Gadre, A. S., & Stilwell, D. J. (2006). Boundary tracking and rapid mapping of a thermal plume using an autonomous vehicle. In OCEANS 2006. https://doi.org/10.1109/OCEANS.2006.306807
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