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Fundamental Equations Guide Marine Robots to Optimal Sampling Sites


Researchers deploy an autonomous underwater vehicle.

Massachusetts Institute of Technology researchers have developed systems of equations that forecast the most informative data to collect during an Unmanned Underwater Vehicle observing mission, and the best way to reach the sampling sites.

Credit: Multidisciplinary Simulation, Estimation, and Assimilation Systems, Massachusetts Institute of Technology

Systems of mathematical equations, developed by Massachusetts Institute of Technology (MIT) researchers, can forecast the most informative data to collect for a given autonomous underwater vehicle's (AUV) mission and the best way to reach the sampling sites.

The MIT team found the new method can predict the degree to which one factor, such as the speed of ocean currents at a specific location, yields information about some other factor, such as the temperature in another location, a quantity called "mutual information."

If a high degree of mutual information exists, then an AUV can be programmed to travel to certain locations to measure one variable, thus gaining information about the other.

The researchers used the equations in an ocean model, called Multidisciplinary Simulation, Estimation, and Assimilation Systems, in experiments to forecast fields of mutual information and guide actual AUVs.

From MIT News
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Abstracts Copyright © 2018 Information Inc., Bethesda, Maryland, USA


 

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