An award-winning industry project with Thales Underwater Systems where I was a key contributor in the development of an AI vision model based on YOLOv5 to recognise concrete cones for a multi-beam sonar on an autonomous underwater drone. We additionally had to manage the LiPo batteries throughout and perform leak tests before each mission. Our efforts were acknowledge by the team both winning the 'Runner's Up Award for best Robotics Project' at UTS Tech Fest 2022, and in all of us receiving a High Distinction for the subject.

A self-led investigation into the benefits of collaboration in autonomous systems. This project challenged me in both time management and technical skill as I had to learn to understand the ROS1 framework and the Turtlebot3s API to create a series of tests during an insanely busy semester. I received a High Distinction for my efforts.

A light-hearted but technical project that challenged us to develop a virtual 1:1 model of both a UR3 and an IRB120 arms on MATLAB using inverse kinematics. We then employed techniques like resolve motion rate control, line plane detection and collision detection to create a solution for owners to play with their pets remotely. The greatest hurdle this subject taught us was to work collaboratively in a software environment.