Updated: 1:01 p.m. Monday, Jan. 16, 2012 | Posted: 4:01 a.m. Monday, Jan. 16, 2012
The Associated Press
BATON ROUGE, La. —
Louisiana State University and Georgia Tech professors are collaborating on a project to improve robots' ability to test for dangerous substances in dangerous places.
The Advocate (http://bit.ly/zx9Mdl) reports that the professors are LSU associate mathematics professor Michael Malisoff and Fumin Zhang, a Georgia Tech assistant professor in the school of electrical and computer engineering.
They have a National Science Foundation grant to find better ways to control robots to make tests in dangerous areas, such as around a wild well on the sea floor.
Zhang says a number of his students already build robots for competitions.
Malisoff specializes in mathematics dealing with control processes such as those that apply to robotics.
Georgia Tech students and College of William and Mary faculty member Mark Patterson also participated in the study.
The idea, they say, is to keep people out of harm's way in the aftermath of emergencies such as the three-month Deepwater Horizon/BP oil leak in the Gulf of Mexico.
Following the Deepwater Horizon three-month oil leak in the Gulf of Mexico in 2010, people in the coastal areas of Georgia were worried the oil would migrate from offshore Louisiana, around Florida and wash up along the East Coast, Zhang said.
Among other concerns, Georgia's coastline is a productive fishing area dependent on good water quality, Zhang said.
"So people there were very worried about this oil spill," Zhang said.
Zhang and a few of his students visited Grand Isle in July, where they completed 21 days of robotics testing while making use of mathematical methods developed by Malisoff.
The National Science Foundation issued a one-year grant for initial research, but Malisoff's National Science Foundation support was extended for another three years to continue the universities' collaboration.
The extended research period will be used to look at time delays between the moment a command is given to a robot and the moment the robot responds to perform the ordered task.
Information from: The Advocate, http://theadvocate.com