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Details of Grant 

EPSRC Reference: EP/R005583/1
Title: Vesca
Principal Investigator: Else, Dr MA
Other Investigators:
Li, Dr B Harrison, Dr RJ
Researcher Co-Investigators:
Dr E Stavridou
Project Partners:
Department: Centre for Research
Organisation: National Inst of Agricultural Botany
Scheme: Technology Programme
Starts: 01 January 2017 Ends: 31 March 2018 Value (£): 119,358
EPSRC Research Topic Classifications:
Control Engineering Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Food and Drink
Related Grants:
Panel History:  
Summary on Grant Application Form
Strawberry harvesting is a manually intensive task that is critically dependent on availability of large volumes of low-cost

labour. Growers are increasingly vulnerable to fluctuations in the labour market and are burdened by the associated high

overheads. Building on Dogtooth's proof of concept strawberry picking robot (developed in Innovate UK project Ananassa),

project Vesca will deliver commercially viable performance through the application of cutting edge reinforcement learning,

to enable efficient motion planning; and computer vision, to locate fruit and determine its suitability for picking. By enabling

the machine's control loops to be closed by the vision system, low compliance, affordable mechatronics are deployed to

deliver a system that has approximately the same performance as a person but at a build cost of £12,000 at scale. In

building a ground truth dataset to train the vision systems cognitive behaviour, NIAB EMR will use their considerable

expertise to develop non-destructive methods for determining fruit quality. Hugh Lowe Farms will deliver commercial

facilities and bench marking to ensure the final system is commercially relevant and viable for large scale trials in the

summer of 2018, enabling them to benefit from this game changing innovation as first adopter.
Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
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