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Agriculture Ladybird robot
Research_

Agriculture and the environment

Pioneering robotics and AI in agriculture
We’re working on a range of innovative projects involving robotics and intelligent software, such as unpiloted air and ground vehicles for farming specialty crops, trees, livestock, and weed management.

Farmers around the world are experiencing a number of pressures including the impact of climate change on crop yields, new pests, shortage of labour, increasing input costs and desires to reduce chemicals.

Air and ground robotic solutions coupled with on-farm artificial intelligence (AI) will have a significant role to play in supporting farmers to address these concerns.

We have been working with growers around the world and funded through a number of grower and government organisations to undertake research, development and operational testing of air and ground robotic solutions.

Our work has also received commercialisation investment.

Our research

Grazing livestock

Robotics and AI for grazing livestock is a very challenging problem because of the difficult terrain and moving animals.

With support from our industry partners we are developing solutions that focus on AI techniques for animal welfare and to assess pasture health.

Our experts: Professor Salah Sukkarieh, Dr Yongliang Qiao, Dr Cameron Clark

Our industry partner: Meat and Livestock Australia (MLA)

We’re investigating how robotic perception technology can improve animal health and welfare in the livestock industries. This MLA-sponsored project is using computer vision and machine learning to develop objective measures of animal welfare from animal appearance and behaviour. Techniques will be refined using data collected in cattle feedlots, with the aim to deploy them remotely in grazing environments later in the project. 

Our experts: Professor Salah Sukkarieh, Dr He Kong

Our industry partner: Agerris

SwagBot is a lightweight electric vehicle fitted with sensors for a range of data collection and farm monitoring tasks in difficult and undulating terrains including livestock location, pasture measurement and farm infrastructure monitoring.

Ground-based platforms can be more beneficial than drones as they have extended range/endurance, whilst having automation capabilities for certain physical tasks, such as targeted weed spraying. The project will demonstrate automated weeding, animal monitoring and energy efficient path planning.

Small holder farmers

We're working with small holder farmers in Australia and around the world to develop innovative and low cost robotic and AI solutions to help them with the many on farm tasks as well as improving crop yields.

Our experts: Professor Salah Sukkarieh, Dr He Kong

Our industry partner: Agerris

The Digital Farmhand is a low-cost electric platform coupled with on-farm AI tools to help small holder farmers assess their crops and undertake tasks such as weeding. This technology suits small holder growers because it is easy to use but also delivers real time information on crop status helping growers detect pests and asses yields.

Forestry

With support from our industry partners, our forestry projects explore the use of sensor-fusion algorithms for estimating forest parameters for high-resolution airborne imagery, light detection and ranging (LIDAR) and photogrammetry.

Our expert: Dr Mitch Bryson

Our industry partners: Forest and Wood Products Australia, NSW Department of Primary Industries, University of Tasmania, SCION New Zealand

Overview: We’re currently developing new 3D pointcloud processing techniques for individual tree detection, segmentation and assessment using aerially-acquired, dense pointcloud datasets from airborne laser scanning.

Aerial systems

We’re working on a range of research projects involving aerial systems to detect, follow and analyse land and animals.

Our expert: Professor Salah Sukkarieh

Our industry partners: Land and Water Australia, The Council of Australasian Weed Societies, Meat and Livestock Australia, NSW Department of Primary Industries, VIC Department of Economic Development, Jobs, Transport and Resources (DEDJTR), QLD Department of Agriculture and Fisheries, Department of Agriculture

We have successfully collaborated for over a decade with various industry partners to research and develop methods algorithms to detect invasive weeds over large areas using drones and machine learning.