Target tracking robot takes inspiration from insect world

The group, which includes engineers and neuroscientists from the University of Adelaide and Lund University, used recordings from the small target motion detector neurons in the brain of a dragonfly to develop a closed-loop target detection and tracking algorithm. To test its performance in real-world conditions, they then implemented the model on a robotic platform that uses active pursuit strategies based on insect behaviour.

The pioneering research, which is published in the Journal of Neural Engineering, is one of the latest efforts to tap into and mimic the incredible abilities of insects. The research also represents the first time that a target-tracking model inspired by insect neurophysiology has been implemented and tested on an autonomous robot.

“Insects, are capable of remarkably complex behavior, yet have a miniature brain consuming tiny amounts of power compared with even the most efficient digital processors,” said Dr Steven Wiederman, who is leading the project in the Visual Physiology & Neurobotics lab of the university of Adelaide.