Robotics and Automation

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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

UK Robotics and Autonomous Systems (RAS) Network -Strategic Task Group in Agri-robotics

A strategic task group in Agri-Robotics (STAR), bringing together robotics, autonomous systems and AI research from around the UK focused on agriculture and the food production pipeline.

Project LeadProfessor Elizabeth Sklar

Funder: Engineering and Physical Sciences Research Council - UK Robotics and Autonomous Systems Network

 

Application of novel machine learning techniques and high speed 3D vision algorithms for real time detection of fruit (Biotechnology and Biological Sciences Research Council – Career Transition Partnership Studentship)

A studentship for research into the application of novel machine learning techniques and high-speed 3D vision algorithms for real time detection of fruit.

Project LeadProfessor Simon Pearson

Funder: National Institute for Agricultural Botany – East Malling Research

 

GRASPberry - High speed picking soft fruit robots

Research to develop the world's first high speed robotic fruit picking system.  Aiming to increase robotic fruit picking speed and develop new ways to detect and pick occluded fruit.

Project LeadDr Grzegorz Cielniak

Funder: UK Research and Innovation – Innovate UK

 

ARWAC Robotic black grass weeder

This research project will develop robotic technology to eradicate the main biotic constraint on UK arable production - a weed 'blackgrass'. Challenges include: route planning, digital mapping, robotic platform development and weed control.

Project LeadDr Charles Fox

Funder: UK Research and Innovation – Innovate UK

 

The First Fleet - The world’s first fleet of multi modal soft fruit robots

This project addresses requirements for fleet robotics for soft fruit production, aiming to develop a fleet of multi modal soft fruit robots.

Project LeadProfessor Marc Hanheide

Funder: UK Research and Innovation – Innovate UK

 

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 LeadProfessor 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 LeadProfessor 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 LeadProfessor 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 LeadProfessor 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 LeadDr 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 LeadDr Amir Ghalamazan Esfahani

Funder: UK Research and Innovation – Research England Connecting Capability Fund - CERES

 

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 LeadDr 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 LeadProfessor 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 LeadProfessor 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 forcasting 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 LeadProfessor 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 LeadDr 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 LeadProfessor 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 LeadDr 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 LeadProfessor 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 LeadProfessor 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 LeadProfessor 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 LeadDr Grzegorz Cielniak

Funder: UK Research and Innovation – Innovate UK