The aim of this project is to develop autonomous systems capable of operating continuously on farms. The goal is to alleviate labour pressures, reduce sources of variability and open up new possibilities in agriculture. Catering to the needs of individual plants or livestock is labour intensive and does not scale up to commercial operations. Currently, at a commercial scale, resources such as fertilisers, pesticides, food and medicine are allocated at inefficient paddock/herd scales. Developing autonomous systems capable of managing farms at the scale of an individual plant/animal would minimise waste, maximise the potential of the farm and reduce environmental impacts. Operating these systems remotely would also allow farmers to manage multiple distant properties while reducing their reliance on transient and unpredictable labour.
To achieve these goals, systems capable of operating in unpredictable and challenging agricultural environments will need to be developed. These systems will need to be equipped with models that can identify agriculturally significant patterns from the data and build predictive models. By equipping these systems with decision models, they will be able to act productively and autonomously on farms. To ensure these systems can operate safely in diverse rural contexts, they will also need to be equipped with models that provide a broad level of situational awareness.
Image credit: Asher Bender