<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-03T15:52:43Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/FFA3AF8D-45E8-4ECA-81BE-68111B19EA93" ns1:id="FFA3AF8D-45E8-4ECA-81BE-68111B19EA93"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/8AC455E1-72C8-4D22-90EE-417AE7794070" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/139BFFC7-EE3F-4010-956C-85147D198324" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/139BFFC7-EE3F-4010-956C-85147D198324" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2024-03-31T00:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/9B6F74AD-7CD0-41C1-96CB-759E353E20DE" ns1:rel="FUND" ns1:start="2023-03-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10060369</ns2:identifier></ns2:identifiers><ns2:title>GRIP-R: Gripper Innovation for the Picking of Recyclables</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>ISCF</ns2:leadFunder><ns2:abstractText>Recycleye presents GRIP-R (Gripper Innovation for the Picking of Recyclables), an AI-driven waste sorting solution with enhanced gripping capabilities that will put the country on track to meet the Plastics Pact target of 70% of plastics packaging effectively recycled, and spearhead the mission to optimise the waste industry's ability to handle the growing issue of contamination caused by film and flexible packaging.

Recycleye has already developed a low-cost, AI-powered system replicating the power of human vision. It uses advanced machine learning algorithms to provide automatic, image-based detection of individual items in co-mingled waste streams, at a material and object level. It leverages a cutting-edge synthetic data generation pipeline, and Recycleye's own WasteNet - the world's largest visual database of labelled waste items, with over 2.5 million images across 28 material classes.

In a previously funded R&amp;amp;D project, Recycleye augmented the vision system with a robotic arm to deliver a robotic sorting solution. Now, Recycleye will push the boundaries of robotics to aim for a higher successful pick rate, leading to more accurate industrial processes and purer material streams circulating in the waste industry, while rapidly expanding the waste industry's films and flexibles handling capacity.

It is traditionally unfeasible to detect and sort films and flexible plastic packaging without extensive manual labour (economically unviable) and these materials are often released into the environment through international waste exports or landfilling. Films and flexibles that do find their way into Material Recovery Facility's (MRFs), are stream contaminants, and can cause significant damage to existing machinery, resulting in blockages and downtime which impacts the recovery of high-value target plastics.

GRIP-R will respond to the challenges posed by film/flexible contamination with exploratory work that results in the redesign of our gripping and pneumatics system to increase material recovery efficiency, while bringing to market the UK's first AI-driven, low-cost, multi-stream robotic sorter which is also equipped to pick and separate films/flexibles.</ns2:abstractText></ns2:project>