Robotics and Automation

Our Research

Robotics and automation is a key strategic theme in the development of innovative solutions to food and farming production. Solutions impact the end-to-end food and farming value chain.

Research Projects

UKRI AI Centre for Doctoral Training in Sustainable Understandable agri-food Systems Transformed by Artificial INtelligence (SUSTAIN)

SUSTAIN imagines a system where data-driven AI transforms the production of crops (selective harvesting and weeding through precision agriculture) and raising of animals (livestock monitoring, reducing animal GHG emissions and improving animal welfare); enhances plant and animal breeding (AI informed genomics); stabilises supply chains (mechanism design and agent-based modelling); reduces fod waste and loss (supply and demand matching) and enables fairer sharing of economic gains and understanding of environmental impacts (ethical and trustworthy AI). All the underlying methods need to be understandable by people so that decisions are trusted (explainable AI).

Project Lead: Professor Simon Parsons

Co-Director: Professor Elizabeth Sklar

Co-Investigator: Louise Manning

Funder: Engineering and Physical Sciences Research Council

An assessment of the viability of inter row cultivations for weed control in commercial narrow row crops in the UK

This project aims to explore how effective inter-row cultivation is in reducing long-term weed populations; whether they can be used to support the use of herbicides, and how the application of this machinery can be maximised within the principles of conservation agriculture.

Project Lead: Dr Shaun Coutts

Funder: Chadacre Agricultural Trust and Felix Thornley Cobbold Agricultural Trust

Gripping Blueberry Harvesters

This project's objective is to develop and demonstrate a fully automatic blueberry harvesting machine, one of the UK's most important soft fruit crops. The proposed machine is developed from prior IUK feasibility study (IUK11295). The project will construct and demonstrate to TRL 7 a full-scale working machine, including full CAD designs for onward manufacturing. It will be fully automatic and include novel berry removal and bush gripper systems to optimise crop quality and productivity at harvest.

Project Lead: Professor Simon Pearson

Funder: Innovate UK

Multi-purpose Physical-cyber Agri-forest Drones Ecosystem for Governance and Environmental Observation

The project will design, build, and test a digital platform for effective, accessible, and secured drone operations and services. The design is based on an innovative platform tried and validated in other European projects and other domains. The added value of this platform will be realised through demonstrated user benefits and reduced risks in drone operations, following EASA guidelines and practices, while it will also follow open-source principles.

Project Lead: Professor Simon Pearson

Co-Investigator: Steve Brewer

Funder: Horizon Europe

From Nitrogen Use Efficiency to Farm Profitability (NUE-Profits) 

A research project that aims to lead to significant improvements in nitrogen and nutrient management while also creating the opportunity for farmers to secure secondary income streams. The project will facilitate farm integration into environmental land management schemes and enhance food security by reducing dependency on nitrogen input costs.

Visit NUE-profits website for more information.

Project Lead: Professor Grzegorz Cielniak 

Funder: Innovate UK, Farming Futures R&D Fund

Intelligent Singulating and Labelling of Developing trees Using Robotics (ISILDUR)

ISILDUR aims to develop an intelligent robotics solution to address endemic labour shortages, focusing on plant processing tasks for the forest nursery sector.

Project Lead: Dr Marcello Calisti

Co-Investigator: Elizabeth Sklar

Funder: Forestry Commission

High-throughput robotic phenotyping of fruit traits for automatic strawberry harvesting

The study will investigate techniques based on plant/fruit geometry (i.e. 3D) providing traits about the phenology of the variety and external fruit and plant characteristics. The approach will overcome the limitations of the laboratory-based phenotyping systems by exploiting an autonomous mobile robot to enable rapid identification of multiple traits in the field.

Project Lead: Professor Grzegorz Cielniak

Funder: Biotechnology and Biological Sciences Research Council

AGRI-OPENCORE. Accelerated delivery of robotic crop harvesting systems for horticulture

AGRI-OPENCORE will create the world's first open development platform (software and hardware) for agri-robotic crop harvesting. 

Project Lead: Professor Grzegorz Cielniak

Co-Investigators: Elizabeth Sklar, Gautham das, Leonardo Guevara, Louise Manning, Marc Hanheide, Simon Parsons, Simon Pearson

Funder: Innovate UK

Agaricus Robotic Harvester

Agaricus Robotics (AR) aims to develop the world's first commercial mushroom harvesting robot, offering end-users game-changing productivity, de-risked labour availability, increased yield, and reduced food waste.

Project Lead: Professor Simon Pearson

Co-Investigator: Bashir Al-Diri

Funder: Innovate UK

Progressive Agri-Robotics Regulatory Network

The aim of this project is to build a Regulatory Science and Innovation Network for the agri-robotics sector.

Project Lead: Dr Leonardo Guevara

Co-Investigator: Simon Pearson

Funder: Innovate UK

Data CAMPP (Innovative Training in Data Capture, Analysis and Management for Plant Phenotyping)

The aim is to develop a suite of units targeting bioscientists at different career stages, covering topics from development and placement of robotics in the field, through to management of phenotyping image sets, and good experimental design for machine learning.

Project Lead: Professor Elizabeth Sklar

Co-Investigators: Oorbessy Gaju, Simon Parsons

Funder: UK Research and Innovation