Automation Opportunities for Reef Restoration

As project specialist in automation for the Reef Restoration and Adaptation Program (RRAP), I identified, conceptualized and budgeted automation opportunities, such as autonomous vehicles, automation-friendly infrastructure, sensors and computer vision, to help scale local reef restoration research projects to production levels that will span across and help save the Great Barrier Reef. Currently, I am helping write and manage the project plans for the development and production of these technologies.

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Automatic Weed Species Detection for Smart Farm Management

The project aimed to develop a precision weed control system in Australian farm pastures using a robot. My role as a research fellow was to advise our industry research partners on their perception systems, data collection and annotation processes. I then developed a deep learning pipeline for automatic weed detection, which is now being used to detect serrated tussock in the field.

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Machine Vision Toolbox for Python

the Machine Vision Toolbox for Python provides many functions useful for machine vision and vision-based control, from photometry to image reading, mathematical morphology and camera calibration. My role as a research associate was to convert Peter Corke’s Machine Vision Toolbox from MATLAB to Python to make the coding aspect of Peter’s Massively Open Online Course (MOOC) course in robotics, vision and control more accessible and open-source.

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