A new robotics project aims to improve productivity and profitability on English soft fruit farms by automating key tasks traditionally carried out by humans.
The Flexbot project brings together agri-tech firms, researchers and growers to develop collaborative logistics robots – known as cobots – capable of transporting fruit and supporting harvest operations.
It comes as growers face rising labour costs, staff shortages and pressure on margins. Partners believe automation could help improve efficiency while reducing waste and speeding the movement of fruit from field to cold storage.
Industry collaboration
The initiative is led by Antobot and funded by Innovate UK. Alongside Antobot, the project includes the University of Surrey, Dogtooth Technologies and the UK Agri-Tech Centre. Three commercial fruit farms will also take part.
The consortium aims to develop an autonomous logistics platform that can integrate technologies from multiple suppliers. It will also explore a business model designed to make robotics more accessible to small and medium-sized growers.
Antobot business director Marc Jones said the goal was to deliver practical automation that improves harvest efficiency, reduces labour pressure and helps protect crop quality through faster on-farm transport.
The University of Surrey has developed an artificial intelligence mapping system known as CueBEV. It combines information from cameras, stereo vision and LiDAR sensors to create detailed maps of fields, crops and obstacles.
Duncan Robertson, founder and chief executive at Dogtooth Technologies, said: “Safe, reliable navigation on outdoor farms remains a critical challenge for the horticultural industry.”
The project is also designed to encourage a wider ecosystem of technology suppliers whose products can be integrated into the platform as growers expand their robotic fleets.
Partners believe the technology could help farmers improve labour productivity, reduce carbon emissions and strengthen the business resilience through gradual investment in automation.