Barriers to adoption of autonomous robots in the soft fruit sector

Panel discussion on overcoming barriers to autonomous robot adoption in soft fruit farms.



As Brexit and Covid pose a double challenge to UK’s agriculture in terms of labour shortages, precision agriculture in the form of autonomous robots in farming seems to hold promise. The high-tech farming initiative dubbed ‘Robot Highways’ is considered to be the world’s largest demonstration of autonomous robots which fuse multiple technologies for operations such as disease treatment (UV treatment for powdery mildew), spraying, crop yield estimation, picking, packing and transportation. Trials are being held on soft fruit farms, particularly on Strawberry fields at Clock House Farm in Kent. The goal of the trial is to ensure sustainable agriculture by addressing labour shortages, food security concerns and reduction of environmental impact of the farm sector.

The ‘Robot Highways’ project funded by Innovate UK, is a collaborative effort of several organisations notably, the University of Reading, University of Lincoln, Saga Robotics, Berry Gardens Growers, The Manufacturing Technology Centre and British Telecom.

The University of Reading is leading grower engagement work as part of the project and the questions before us are how will such high-tech farming practices affect growers? What challenges will growers face in the adoption of such technologies? To deliberate on such issues the research team is organising a panel discussion on overcoming barriers to autonomous robot adoption in soft fruit farms.

We have an online panel of experts from the worlds of academia, industry, funding, and growing. Mondira Bhattacharya will give a short update on the user engagement so far as part of Robot Highways.

The panelists include

David Rose, University of Reading (Chair)
Simon Pearson, University of Lincoln
Halvard Grimstad, Saga Robotics
Coral Clark, British Growers Association
Katrina Hayter, Innovate UK

The event is finished.


Nov 09 2021


5:00 am - 6:00 am

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