Leopard sharks aren’t the fastest fish in the sea. That fact might keep them from medaling in any speed-based shark competitions, but it makes them ideal candidates for tracking.
Using money from the awesomely named National Science Foundation’s Robust Intelligence Program, a team of students and faculty from Cal Poly and CSU Long Beach recently tracked a leopard shark caught in Seaplane Lagoon near Alameda. They reported capturing a 1-meter long leopard shark (that’s a little longer than 3 feet) over the summer, tagging it with an acoustic emitter, and releasing it.
They followed the shark with a torpedo-like autonomous underwater vehicle—also an awesome name—which gathered information about the fish and its environment. Participants hope to learn more about what might impact sharks’ migration patterns and whether different tracking methods alter shark behavior.
The autonomous vehicle can be programmed to follow a tagged shark, then return to the researchers. The researchers will compare the data they collected this summer against information collected earlier by Long Beach researchers who followed a similar shark by boat.
Cal Poly computer science professor Chris Clark and marine biology professor Mark Moline are working with CSU Long Beach marine biology professor Christopher Lowe on the project, with funding from a three-year, $490,000 grant.
Clark reported that he and a team of students working in Cal Poly’s Lab for Autonomous and Intelligent Robotics are advancing robotics technology, specifically in the areas of new estimation and control theory.
Cal Poly computer science students Christina Forney and Esfandiar Manii, Harvey Mudd student Chris Gage, and CSULB student Mike Farris all pitched in for the shark-stalking effort. Clark gave particular kudos to Forney and Manii’s engineering and computer programming.
The group’s vehicle was equipped with something called a stereo-hydrophone system that figures out which direction a tagged shark lies based on how it receives acoustic signals. Students developed an algorithm that lets the machine estimate where the shark is in real time.
Roy Scheider, rest in peace, would be proud.
For more information about Cal Poly’s hand in the project, visit lair.calpoly.edu (to learn about autonomous underwater vehicles) or marine.calpoly.edu (to learn about sharks—or the Cal Poly Center for Coastal Marine Sciences).
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