Robot to save Barrier Reef from starfish vandalism

Queensland University of Technology roboticists have developed COTSbot, the world’s first robot designed to control populations of crown-of-thorns starfish on the Great Barrier Reef.

According to QUT, crown-of-thorns starfish (COTS) are responsible for an estimated 40 per cent of the reef’s total decline in coral cover. To counter this, roboticists have spent the last six months developing and training the robot to recognise COTS among coral in order to reduce the damage they cause.

Dr Matthew Dunbabin from QUT’S Institute for Future Environments, said the COTSbot is equipped with stereoscopic cameras to give it depth perception, five thrusters to maintain stability, GPS, pitch-and-roll sensors and a unique pneumatic injection arm to deliver a fatal dose of bile salts.

Drs Matthew Dunbabin (left) and Feras Dayoub (right) have developed the COTSbot, the world's first robot designed to control the Great Barrier Reef’s crown-of-thorns starfish population
Drs Matthew Dunbabin (left) and Feras Dayoub (right) have developed the COTSbot, the world’s first robot designed to control the Great Barrier Reef’s crown-of-thorns starfish population

The roboticists believe COTSbot is the first autonomous underwater vehicle to be equipped with an injection system. It’s also designed to operate exclusively within a metre of the seafloor, one of the most challenging environments for any robot.

Dr Feras Dayoub, from QUT’S Science and Engineering Faculty who designed the COTS-detecting software, said the robot would continue to learn from its experiences in the field.

“Its computer system is backed by some serious computational power so the COTSbot can think for itself in the water,” he said in a statement. “If the robot is unsure that something is actually a COTS, it takes a photo of the object to be later verified by a human, and that human feedback is incorporated into the robot’s memory bank. That in itself is quite an accomplishment given the complexity of underwater environments, which are subject to varying visibility as well as depth-dependent colour changes.”

Dr Dunbabin added: “Human divers are doing an incredible job of eradicating this starfish from targeted sites but there just aren’t enough divers to cover all the COTS hotspots across the Great Barrier Reef.

“We see the COTSbot as a first responder for ongoing eradication programs – deployed to eliminate the bulk of COTS in any area, with divers following a few days later to hit the remaining COTS.

“The COTSbot becomes a real force multiplier for the eradication process the more of them you deploy – imagine how much ground the programs could cover with a fleet of 10 or 100 COTSbots at their disposal, robots that can work day and night and in any weather condition.”

The COTSbot completed its first sea trials in Queensland’s Moreton Bay to test its mechanical parts and navigation system. The key to the autonomous underwater vehicle is its new computer vision and machine learning system.

Dr Dunbabin first built a vision system for detecting COTS from underwater images ten years ago but shelved the idea of building a robot due to the limitations of the eradication methods in use, which required divers to inject each COTS up to 20 times. However a breakthrough from James Cook University (JCU) last year allowed him to refloat the project.

“I was really pleased to hear about JCU’s announcement last year of a one-shot injection method had proved just as effective,” he said. “That was the game changer that opened the doors for a robotic solution to the COTS problem. Combining this with new advances in machine learning meant we could make COTSbot a reality.”

The QUT roboticists plan to take COTSbot to the Great Barrier Reef later this month to trial it on living targets. In that trail, a human will verify each COTS identification the robot makes before the robot is allowed to inject it.

The COTSbot is planned to be working the reef autonomously by December and the roboticists are seeking funding to scale up the manufacturing and deployment of the COTSbot.