Selective Harvesting

Our Research

Robotic applications for crop harvesting. Developing systems which identify harvest ready crops to enable reliable and consistent picking/harvesting. This uses a mix of practical engineering solutions, robotics, vision and sensing systems, data collection sensors, and computer science, to design, develop, and deliver effective and consistent data and technology driven solutions.

Research Projects

Optimising the light recipe for maximum photosynthesis yield and quality in strawberry (UK Research and Innovation - Biotechnology and Biological Sciences Research Council – Career Transition Partnership Studentship)

UK Research and Innovation - Biotechnology and Biological Sciences Research Council – Career Transition Partnership funding for a studentships on "Optimising the light recipe for maximum photosynthesis, yield and quality in strawberry".

Project Lead: Professor Simon Pearson

Funder: National Institute for Agricultural Botany – East Malling Research

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 food 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

Agri-Robotics Unleashed (ARU)

Agri-Robotics Unleashed (ARU) is a whole systems approach that drives soft fruit sustainable productivity by integrating robotic harvesting solutions into greenhouse design and novel canopy architectures.

Project Lead: Dr Marcello Calisti

Co-Investigators: Grzegorz Cielniak, Leonidas Rempelos, Simon Pearson

Funder: Biotechnology and Biological Sciences Research Council

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

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

Qualicrop

To develop and introduce farm-gate, just in time automated crop grading for delicate produce (e.g. strawberries and grapes), adding value for tight-margin growers and ultimately disintermediating an inefficient supply chain, lowering costs to consumers.

Project Lead: Professor Grzegorz Cielniak

Co-Investigator: Simon Pearson

Funder: Innovate UK

FinerForecasts – Biologically Driven Soft-Fruit Resource Optimisation, Labour and Yield Forecasts at Plant Granularity

FinerForecasts will leverage FruitCast's ability to quickly and cheaply measure crop state from videos to make plant-level forecasts possible at commercial scales.

Project Lead: Dr Shaun Coutts

Co-Investigator: Grzegorz Cielniak

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