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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 labour intensive task that depends critically on the availability of a large amount of low-cost labour. Growers are increasingly vulnerable to labour market price fluctuations and burdened by high employment overheads. Building on Dogtooth's proof of concept strawberry picking robot (developed during Innovate UK project Ananassa), project Vesca will deliver commercially viable picking performance using cutting edge machine learning and computer vision techniques to facilitate more efficient localization of target fruit (by more nearly optimal control of robot motion) and more accurate determination of suitability for picking. The project will also provide ancillary benefits such as yield mapping and prediction that are of significant importance to growers.
Key Findings
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Summary
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