Real-time semantic perception for autonomous field robotics

This project will focus on augmenting our current perception system by semantic information that will be derived from 4D+ data using the latest machine learning techniques. This will help the robots to better understand their environments beyond just the 3D geometry, thereby allowing them to achieve even more complex missions and effectively.

As a PhD candidate, you will research, implement, and demonstrate advanced visual odometry systems for use on a variety of autonomous platforms, including drones and ground robots such Spot from Boston Dynamics. You will be part of a world class autonomy team with researchers and engineers from Emesent and QUT who are pushing the state of the art in autonomous systems and artificial intelligence.

If the combination of robotics, autonomy, ML/AI and cutting-edge research appeals to you, then we would love to hear from you.

 Fully funded and top-up scholarships are available with this project.

Chief Investigators