Students Mike Farris, Christina Forney and Esfandiar Manii observe an autonomous underwater vehicle in operation during a test of the new shark-tracking device off the coast of Long Beach.
Tracking sharks may become easier soon as the result of a project involving students and faculty from Cal Poly and Cal State Long Beach.
The shark tracking project uses autonomous underwater vehicles, or AUVs, from Cal Poly to gather and send data to scientists, said Chris Clark, a Cal Poly computer science professor. Clark and marine biology professor Mark Moline are collaborating with CSULB marine biology professor Christopher Lowe on the project funded by a three-year, $490,000 grant from the National Science Foundation's Robust Intelligence program.
Previously available technology required scientists to follow sharks in small boats to track electronic signals sent from tags attached to the fish. But Clark said the AUVs, which resemble small torpedoes, can be programmed to follow tagged sharks, then return to researchers.
As a result, scientists may be able to follow sharks across longer distances and for longer time periods, Clark said. AUVs are equipped with sensors that detect and report on the sharks’ environment, providing information about factors that may influence their migration patterns.
For the project, Clark and a team of students in Cal Poly’s Lab for Autonomous and Intelligent Robotics, or LAIR, are advancing robotics technology, specifically in the areas of new estimation and control theory, Clark said.
Over the summer, Clark and Lowe worked with Cal Poly computer science students Christina Forney and Esfandiar Manii, Harvey Mudd College student Chris Gage and CSULB student Mike Farris to test the AUVs and track a leopard shark off the coast of Long Beach. The team caught a 1-meter-long leopard shark in Sea Plane Lagoon, tagged it with an acoustic emitter and released it. They then used an AUV to track it.
Following the successful test, the team is comparing the information generated using the AUV against earlier data collected by CSULB researchers who followed a leopard shark by boat. The research also may indicate whether shark behavior is affected by tracking methods.
Clark credited much of the experiment’s success to the engineering and computer programming done by Forney and Manii.
Leopard sharks were chosen for initial tracking experiments because of their limited speed and distance traveled, Clark said.
The AUV was equipped with a stereo-hydrophone system that determines a direction to the tagged shark based on when signals arrive at each of the hydrophones. Clark said the AUV also runs a filtering algorithm, developed by students, that allows the underwater robot to estimate the location of a shark in real time.
The AUV can be driven manually through wireless communication on the surface and programmed for missions that allow it to navigate from waypoint to waypoint. A secondary processor makes it fully programmable, as well.