Breakthrough for researchers in UAV object detection system project with Boeing Australia

QUT researchers  including QCR Executive member and Chief Investigator, Professor Jason Ford and colleagues Dr Tim Molloy and Dr Jasmin Martin have developed an algorithm used in an unmanned aerial vehicles (UAVs) object detection system.  They used a complex maths model called the Hidden Markov Model (HMM) to develop the algorithm that enables UAVs to replicate a human pilot’s ability to visually detect aircraft at a range of more than 2km.

This was key barrier to fully achieving the global commercial market of unmanned aerial vehicles.

“We’ve been working on this problem for 10 years and over that time 50 people or more have been involved in this project,” Professor Ford said.  “We are leading the world in solving the extremely challenging problem of replicating the role of a pilot’s eye.

HMMs were developed in the 1960s and allow people to predict unknown, or hidden, variables from observed information.

Professor Ford said although most people outside of the maths community would not have heard of HMMs, they would have benefited from its many applications in economics, neuro-biology and telecommunication and examples as broad as in DNA sequencing to speech recognition systems used by smart phone digital assistants.

The breakthrough is the latest step after a series of related research projects in the past decade, including the Smart Skies Project and Project ResQu in collaboration with Boeing Australia and Insitu Pacific.

Read more: Maths model the key to aerial detection system