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for Robotic and Autonomous Perception This project aims to make robotic perception systems safer and more reliable by developing new techniques that continuously monitor the performance of their machine
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future autonomous instrument control and self-directed experimentation will be developed, recognizing the challenge presented by the integration of multiple complex systems. Coding and user interface
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for future autonomous instrument control and self-directed experimentation will be developed, recognizing
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novel opportunity to automate and improve the frailty assessment process, aiming for greater consistency and predictive accuracy. Aims i) Develop a deep learning algorithm to autonomously detect and
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industries which are the industrial driving forces for Australia. The invented technologies will help autonomous underwater vehicles to look for submerged resources, and aid resource exploration and extraction