Award details

16AGRITECHCAT5: 3D Vision-based Crop-Weed Discrimination for Automated Weeding Operations

Reference	BB/P004911/1
Principal Investigator / Supervisor	Dr Grzegorz Cielniak
Co-Investigators / Co-Supervisors	Professor Tom Duckett, Professor Simon Pearson
Institution	University of Lincoln
Department	School of Computer Science
Funding type	Research
Value (£)	89,532
Status	Completed
Type	Research Grant
Start date	01/09/2016
End date	09/01/2018
Duration	16 months

Abstract

This project will investigate technical foundations for the next generation of robotic weeding machinery enabling selective and accurate treatment of individual weeds. The investigated technology is a novel combination of low-cost 3d sensing and learning software together with a suitable weed destruction technique. The proposed developments will lead to more efficient cultural weeding equipment resulting in better management of weeds and reduced input use bringing several benefits to good producers, sellers and society.

Summary

Impact Summary

The project has the potential to derive a high level of economic and social benefit. The proposed technological solution for robotic cultural weeding machinery will result in reduced input use and increased efficiency in primary crop production and indirectly also in sustained food quality and safety. The potential products will have positive impact on the entire UK Agri-Tech sector and its one representative in particular, Garford Farm Machinery. The economic benefits will be also felt by food producers, sellers and consumers. The impact of this proposal in terms of the industry and social consequences are very high, but the project carries some risk as the main challenge has yet to be resolved. On this basis we believe that the project is highly appropriate for public funding from Innovate, and should provide a high level of return. There is no doubt that there are many challenges which the UK agriculture face in terms of developing improved vision analysis and robotic weeding systems. This project will help develop further capacity in a key industry area which is required to achieve the general government objective of the sustainable intensification of UK agriculture. A key positive step of this proposal is that is facilitates the transfer of the robotic and computing skills of the University of Lincoln into Garford Farm Machinery Ltd.

Committee	Not funded via Committee
Research Topics	Crop Science, Plant Science
Research Priority	X – Research Priority information not available
Research Initiative	Agri-Tech Catalyst (ATC) [2013-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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