Agriculture

Autonomous systems can help to transform agriculture. From fruit picking, to forecasting, to inspection and monitoring, the use of such technology must be proven to be safe before its introduction and adoption.

This section pulls together all the research taking place in the agriculture domain. It also highlights cross-domain work which will be of use to those focused on this sector.

Where possible, a lot of the guidance we publish is intentionally developed to be suitable for use in any domain. You will therefore find key pieces of research below that are suitable for those working in any sector.

Image of guidance website - www.assuringautonomy.com

Expert guidance

We have created a guidance website that is home to our expert guidance on the safety assurance of autonomous systems, including an interactive version of AMLAS, our methodology for assuring the safety of machine learning components.

Go to the website
(external site)

Body of Knowledge guidance

The guidance in the Body of Knowledge is often generalised, enabling you to learn from research undertaken in other domains. At present we do not have any guidance in the BoK based on research in the agriculture domain, so below you can access a number of entries that provide cross-domain guidance. You can also access all Body of Knowledge Guidance.

1.2 Identifying hazardous system behaviour
1.4 Impact of security on safety
2.2.4.3 – Verification of deciding requirements
2.3.1 Sufficiency of training data

Latest research papers

Here are the most recent papers from our agriculture demonstrator project. You can also view all of our research papers.

Khalid, M., Guevara, L., Hanheide, M., Parsons, S. Assuring autonomy of robots in soft fruit production, 4th UK-RAS Conference for PhD Students & Early-Career Researchers, 2021.
Guevara, L., Khalid, M., Hanheide, M., and Parsons, S. Assessing the probability of human injury during UV-C treatment of crops by robots, 4th UK-RAS Conference for PhD Students & Early-Career Researchers, 2021.