Small to medium-sized fixed-wing unmanned aircraft vehicles (UAV) have an incredible range of potential applications in civilian operations including:
- disaster assessment
- search and rescue
- environmental and infrastructure monitoring
- remote sensing in agriculture
- product delivery.
The national airspace is heavily regulated with strict rules and safety layers that aim to mitigate the risk of mid-air collisions. The final safety layer corresponds to human pilots using their eyes and judgment to avoid potential mid-air collision threats.
Sense and avoid (SAA) refers to the implied regulatory requirement that UAVs be capable of sensing and avoiding potential mid-air collisions threats. The development of systems capable of matching and exceeding the reported performance of human pilots and meeting the implied SAA regulatory requirement is one of the key technical challenges hindering the routine, standard and flexible operation of UAVs in the national airspace.
While there's been significant progress over the last decade with narrow field of view (FOV) sensors, it's still difficult to replicate a human pilot's ability, using computer vision, to sense potential aircraft at ranges exceeding 2km from a wide field of regard.
This project will research how to achieve long-range aircraft detection from an image sequence taken from a wide FOV sensor.
This will involve investigating candidate image processing approaches. This will build from what is already known about narrow FOV image-based aircraft detection.
Key aspects of this project will relate to discovering how to replace the planar image homography operation and the detection of very small and low signal-to-noise ratio objects from distorted image sequences.
We expect to develop new algorithms and technology contributing to the improvement of UAV operations and safety.
Skills and experience
We expect you to have experience/skills in:
- algorithm development
- C and C++ programming
You may be able to apply for a research scholarship in our annual scholarship round.
Contact the supervisor for more information.