Overview
Topic status: We're looking for students to study this topic.
Project summary
Machine vision is emerging as a promising technology for reliably detecting and tracking aircraft in mid-air collision scenarios. In recent research projects, we have investigated machine vision for the purpose of daytime 'sense-and-avoid' in both manned and unmanned aerial vehicles.
Project aims
This project will investigate the performance of our currently proposed techniques in adverse environmental conditions. The significance of this research project lies in addressing the questions:
- How well do existing vision-based aircraft detection techniques perform on overcast days and starry nights?
- How can vision-based aircraft detection be performed more effectively in these adverse environments?
The key tasks associated with answering these questions will include organising and processing image data from previous flight trials, and collecting new data from a ground-based camera near Brisbane airport.
Student requirements
You must have basic knowledge of MATLAB and/or C++.
No aerospace experience is necessary.
This is a 12 week project (Mid November 2012 to February 2013). Hours are negotiable.
- Study level
- Vacation research experience scholarship
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Keywords
- aircraft detection, mid-air collision, machine vision
- Contact
- Contact the project supervisor for more information.
Dr Jason Ford
