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
Building a better blueberry harvester (Award acceptance)
A research project to develop and demonstrate a fully automatic blueberry harvesting machine. Blueberries are one of the UK's most important soft fruit crops. Challenges include: energy utilisation, image analysis and the development of shaking systems.
Project Lead: Professor Ronald Bickerton
Funder: UK Research and Innovation – Innovate UK
Interreg North West Europe - COTEMACO (increased competitiveness through efficient man and machine collaboration) project
A research project focused on the use of collaborative robots in the food industry.
Project Lead: Professor Simon Pearson
Funder: Interreg North West Europe
Mobile Robotic Platforms for Active Inspection and Harvesting in Agricultural Areas
BACCHUS. Research to deliver an intelligent mobile robotic system for harvesting of grapes - for viticulture and for table grape production. Working with industrial partners to develop robotic solutions.
Project Lead: Professor Marc Hanheide
Funder: European Commission – Horizon 2020 programme
Digitising Cacao production in Colombia
This project aims to deploy a Wireless Sensor Network (WSN) to monitor cocoa plantations in Colombia. Challenges include: sensing systems, predictive analytics and data handling.
Project Lead: Professor Simon Pearson
Funder: UK Research and Innovation – Innovate UK
SHAPE - Strawberry Harvester for Polytunnels and Open Fields
SHAPE will develop the first complete system for harvesting strawberries grown in strawberry tunnels and in open fields. This project addresses the research required to close the technological gaps that will take this to a commercial product.
Project Lead: Dr Grzegorz Cielniak
Funder: EEA and Norway Grants
"RoboFruit" – Universal robotic fruit picking head
We aim to develop a universal picking head, to harvest ripe fruit. Long-term environmental benefits will be reduced food waste through better crop utilisation.
Project Lead: Dr Amir Ghalamazan Esfahani
Funder: UK Research and Innovation – Research England Connecting Capability Fund - aCERES
FASTPICK: Novel active vision and picking head to robotically harvest soft fruit
FASTPICK will develop active vision systems integrated to a novel robotic picking head that aims to pick 95% of fruit to c. 2 seconds per berry, the same performance of human harvesters. This performance removes the final technical barrier to large scale adoption of agri-robotic systems for the soft fruit sector.
Project Lead: Dr Amir Ghalamazan Esfahani
Funder: UK Research and Innovation – Innovate UK
AI Unleashed
Artificial intelligence has the potential to transform agriculture. However, AI is not reaching its full potential because the processing speed on machines is a significant bottleneck. This project looks at improving processing speeds for data handling.
Project Lead: Professor Elizabeth Sklar
Funder: UK Research and Innovation – Research England Connecting Capability Fund - CERES
Robot Highways
This project aims to develop a knowledge exchange platform to empower transformation across UK and global supply chains. The platform will underpin industry sustainability by reducing sector reliance on low skilled labour, whilst upskilling the existing workforce.
Project Lead: Professor Marc Hanheide
Funder: UK Research and Innovation – Innovate UK
Find out more: Hear more about the project including the impacts at Clock House Farm in Kent during a BBC Radio 4 broadcast, On Your Farm, Robot Highways.
FRUITCAST
This project addresses the forecasting of readiness of commercially grown strawberries. Our technology led system integrates farm data on a deeply granular level, aiming to decrease the uncertainty of forecasts by monitoring the crop responses in real-time.
Project Lead: Professor Simon Pearson
Funder: UK Research and Innovation – Research England Connecting Capability Fund - CERES
Autonomous black grass detection
This project aims to develop and verify an automated system for rapid black-grass detection in new fields at plant level. The long-term benefits of the project will be to reduce risk of herbicide resistance and environmental contamination while protecting long-term yields.
Project Lead: Dr Shaun Coutts
Funder: UK Research and Innovation – Research England Connecting Capability Fund - CERES
The Augmented Agronomist - Synthesis of AI, ML and Robotics for Decision Support (UK Research and Innovation - Biotechnology and Biological Sciences Research Council – Career Transition Partnership Studentship)
This project sets out to provide agronomists with dedicated technological support in assessment and decision making. The project is closely linked with the RASberry project and will have access to its software and hardware resources to minimise risks and maximise synergies.
Project Lead: Professor Marc Hanheide
Funder: National Institute for Agricultural Botany – East Malling Research
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
BerryPredictor - improving harvest forecasts, yield predictions and crop productivity by optimising zonal phytoclimates in covered strawberry production
There is increasing consumer and retailer demand for high-quality UK-grown strawberries. The challenge is to achieve consistently high yields and quality across variable and challenging growing seasons. BerryPredictor aims to provide UK growers access to real-time accurate yield prediction profiles.
Project Lead: Professor Simon Pearson
Funder: UK Research and Innovation – Research England Connecting Capability Fund - CERES
In field logistics for fruit production
University of Lincoln and industrial partners have recently completed an UK Research and Innovation - Innovate UK project using a robotic platform as an autonomous vehicle to support picker logistics. The robot will now be framed to enable full scale, rapid deployment.
Project Lead: Professor Marc Hanheide
Funder: Berry Gardens Ltd
VEGCAST - Forecasting harvest profiles for broccoli
VEGCAST will develop state-of-the-art crop forecasting technology that combines camera based machine learning technology with multi-ensemble meteorological predictions. These forecasts will enable growers to better match supply and demand, thereby reducing waste and minimising supply chain friction.
Project Lead: Professor Simon Pearson
Funder: UK Research and Innovation – Research England Connecting Capability Fund - CERES
Development and field testing of the next generation of vision guided weeding systems
This project will develop the next generation of weeding machinery based on a precision hoe tightly controlled by an intelligent vision system to assure high accuracy of hoeing operations.
Project Lead: Dr Grzegorz Cielniak
Funder: UK Research and Innovation – Innovate UK
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.
Project Lead: Professor Grzegorz Cielniak
Funder: Innovate UK, Farming Futures R&D Fund
Visit https://www.nue-profits.com/ for more information.