With the expertise of internationally recognised researchers into field robotics, particularly environmental robots, and their application to large-scale marine habitat monitoring, marine pest (Crown-of-Thorns Starfish) control, and aquatic greenhouse gas mapping, such as Dr Matthew Dunbabin. He and his team have expertise in adaptive sampling and path planning, vision-based navigation, cooperative robotics, as well as robot and sensor network interactions.
Current projects in marine robotics include successfully testing COTSbot on the Great Barrier Reef, and extending this success to produce the smaller version, RangerBot.
We welcome industry collaborations in this field. For more information about collaborating with our team, please contact us.
This project is developing new techniques for automated early detection of the invasive grass African Lovegrass, using methods ranging from machine learning to psychophysics.
03/01/2016 - 08/01/2019
LunaRoo was started as a proposal for the Lunar Payload Opportunity by the Google Lunar X Prize team scientists.
COTSbot seeks out and controls the Great Barrier Reef's crown-of-thorns starfish (COTS), which are responsible for an estimated 40 per cent of the reef's total decline in coral cover.
The Inference boats are designed to be our eyes, ears and nose on waterways, 24 hours a day - rain, hail or cyclone.
RangerBot is a low-cost, vision-enabled autonomous underwater vehicle for monitoring a wide range of issues facing coral reefs across the globe.
Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation
The aim of this research is to explore and developed a system which includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas.
Plant Biosecurity CRC
The aim of this project is to develop a system which combines new detection methods (UAVs and specialised sensors) with advanced modelling techniques to determine high-risk areas for pest risk surveillance, namely buffel grass.
This project designed a system to detect bitou bush in coastal dunes using unmanned aircraft and machine learning classification algorithms towards the development of a flexible approach to monitoring and track similar weeds of interest in New South Wales and Queensland.
Aerial Mapping of Forests Affected by Pathogens using UAVs, Hyperspectral Sensors and Artificial Intelligence: Myrtle Rust
This project aims to provide end-users with the value of these technologies in guiding decisions and adopting systems based on capabilities to detect exotic pathogens on host plantation and natural forests.
Assessing the capabilities of digital imaging and Unmanned Aerial Systems (UAS) for species management
Logan, Tweed Shire and Gold Coast City Council
The key aim of this Project is to assess the utility of digital imaging for the cost effective detection and assessment of koala abundance in Tweed, Gold Coast and Logan local government areas (LGAs) using an innovative approach which combines Unmanned Aerial Vehicles, digital imaging, and statistical modelling.
The aim of this project is to predictive models and deep learning combined with high resolution hyperspectral detection technologies to increase surveying efficiency and to develop methodology for aerial coral bleaching detection.
This project demonstrated that the PNC sampled with a constant traffic flow, increased from a concentration of 2×104 p/cm^3 near the ground up to 10 m, and then sharply decreased attaining a steady value of 4×103 p/cm^3 beyond a height of about 40 m.
This cross disciplinary project aims to develop, validate and implement novel methods for high sensitivity atmospheric sensing and apply cutting-edge statistical and analytic techniques to the data sets, unprecedented in scope and resolution.
The aim of this research was to establish the best mounting point for four gas sensors and a Particle Number Concentration (PNC) monitor, onboard a hexacopter, so to develop a UAV system capable of measuring point source emissions.
Securing Antarctica’s Environmental Future (SAEF) is an Australian Research Council Special Research Initiative that aims to strengthen Antarctic science, policy and governance at a time of rapid environmental and geopolitical change.
Commonwealth Grant CRCPIX000099 (Cooperative Research Centre Project); Agent Oriented Software (Lead Partner)
The project aims to develop a robot to autonomously find and identify individual noxious weeds, spraying or using an alternative method to eliminate them. It will produce a series of operational prototypes ("Kelpie"), based upon a commercially available agricultural chassis.