For defence applications, for surveillance, for self-driving cars and for tracking real-world natural phenomena, Associate Professor Brinkworth and his colleagues are creating new technologies and robotic systems that are autonomous and adaptable.
Their recent work has focused on creating systems that can detect changes in the environment, such as scanning for unauthorised drones at airports and military sites.
Current surveillance systems typically consist of high-grade cameras that collect visual information. Images are analysed by artificial intelligence trained to classify objects based on their appearance – distinguishing a drone from a bird, for example.
“But it’s really resource intensive and relatively slow to scan the entire environment at high resolution all the time,” Associate Professor Brinkworth says. “We’ve developed a system that operates much faster.”
The key is an approach based on the biological reality of how eyes work. Low-grade vision is applied as a first-pass scanning tool (equivalent to peripheral vision that animals and insects use) and then the system shifts to higher resolution vision (known as a foveal vision by biologists) once something new is detected.
“It’s a much more efficient way to do surveillance,” Associate Professor Brinkworth says.
Putting this new technology into action, Associate Professor Brinkworth has developed software that can be retrofitted to existing high-grade detection cameras to extend their capabilities.
“We’ve done simulations and real-world trials at Woomera in regional South Australia that show we’re able to track drones out 50% further than other systems are able to do – so a detection system that worked over 2km can now operate at 3km,” Associate Professor Brinkworth says. “This has real-world applications for perimeter defence and airport monitoring, where unwanted drone activity needs to be detected.”
The system is incredibly robust, with three modes of detection built in.
“We can track drones visually, by their heat signature and by their sound, meaning it’s very hard to evade this system,” says Associate Professor Brinkworth.