Tracking the movements of sharks may soon become easier, thanks to a project involving students and faculty from Cal Poly San Luis Obispo and CSU Long Beach.
Cal Poly Computer Science Professor Chris Clark and Marine Biology Professor Mark Moline are collaborating with CSU Long Beach Marine Biology Professor Christopher Lowe on the shark tracking project, which involves using Autonomous Underwater Vehicles (AUVs) from Cal Poly. The AUVs, which resemble torpedoes, gather and send data to scientists.
Until now, existing technology has required scientists to follow sharks in small boats in order to track electronic signals sent from tags on the fish. The AUVs can be programmed to follow tagged sharks and then return to researchers. The underwater marine robots have the potential to allow scientists to follow sharks across longer distances and for longer time periods.
The AUVs are equipped with sensors that detect and report on the sharks’ surrounding ocean environment, providing information about factors that may influence their migration patterns.
For the project, Clark and a team of students working in Cal Poly’s Lab for Autonomous and Intelligent Robotics (LAIR) are advancing robotics technology, specifically in the areas of new estimation and control theory, Clark said.
The research may also indicate whether shark behavior is affected by tracking methods.
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.
Leopard sharks were chosen for initial tracking experiments because of their limited speed and distance traveled.
The AUV was equipped with a stereo-hydrophone system that determines the direction of the tagged shark based on differences in acoustic signal arrival times at each of the hydrophones. The AUV also runs a filtering algorithm, developed by students, that allows the AUV to estimate the location of a shark in real time.
SOURCE: Cal Poly