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Intelligent and Smart Robots for Undersea Survey Operations

by Savitha C Muppala on December 7, 2011 at 8:55 PM
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 Intelligent and Smart Robots for Undersea Survey Operations

Researchers have developed a novel software that can make robots smarter during undersea survey operations.

Researchers at the Massachusetts Institute of Technology (MIT) and University of Southern California (USC) developed a persistent surveillance theory that provides a framework for decision-making software that maximizes a robot's collection of information over a given area. It gives some guarantees on performance in dynamic environments.


"The ability to do surveillance that takes into account the actual conditions of the environment brings a whole new level of automation and capability," Daniela Rus, co-director of MIT's Computer Science and Artificial Intelligence Laboratory Center for Robotics, said.

"We have come up with a solution that lets the robot do local reasoning to make decisions and adjust the path autonomously without having to come up to the surface to interact with humans," she said.

The scientists produced an algorithm that incorporates both the user's sensing priorities and environmental factors, such as ocean currents, into a computer model to help undersea robots conduct surveys and mapping missions more efficiently.

Tests proved the benefits of using the new algorithm. The scientists conducted two separate experiments using underwater robots called gliders, operated by oceanographers. They used two gliders, one with the algorithm and one without, to measure whether the experimental technology yielded better maps of algae blooms and other underwater phenomena in the Pacific Ocean.

"In areas where the oceanographers wanted more information, the persistent surveillance algorithm actually produces more detail," Gaurav S. Sukhatme, ANTIDOTE's principal investigator and director of USC's Robotic Embedded Systems Lab, said.

"The system can automatically figure out how to divide its time between areas that are more interesting and areas that are less interesting," he said.

The algorithm helps the gliders decide when to spend more time looking at regions that have changes in activity or environmental factors.

Without the control algorithm, gliders paid equal attention to all areas and acquired less information during the experiments in Monterey Bay, Calif., and along the southern coastal waters near Los Angeles in October and November 2010.

Source: ANI
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