Imagine a smart robot that can look at a pile of electronic junk and instantly know exactly where the valuable magnets and rare metals are hidden. Instead of people doing the dangerous work of taking apart old cars or phones by hand, these robots learn how to dismantle them precisely. It is like giving a recycling center a brain and a pair of expert hands to find hidden treasures in trash.
Current waste sorting relies on expensive manual labor or machines limited to only 3 waste streams. This makes recovering high-value critical raw materials from complex electronics and vehicles inefficient and slow.
An integrated platform combining AI, spectral sensors, and robotic arms capable of dismantling products and picking specific materials in real-time.
If you are an ELV processor dealing with the slow manual removal of electric motors — this project developed self-learning robots that dismantle motors to recover neodymium magnets. This replaces heavy manual sorting with precise robotic picking.
If you are a WEEE recycling plant dealing with mixed electronic waste streams — this project developed an AI-powered sensing platform that detects hazardous components and critical raw materials. This allows for automated sorting beyond the current limit of three streams.
If you are a waste contractor dealing with high volumes of urban waste — this project developed a robotic system integrating spectral sensors and AI to locate valuable materials in real-time. This reduces the reliance on trained staff for manual sorting before incineration.
Based on available project data, specific pricing or cost details for the robotic systems are not provided.
Yes, the project is validating solutions across 4 large-scale pilots in Spain, Portugal, Greece, and Turkey to ensure scalability and industrial viability.
Based on available project data, specific IP and licensing terms are not mentioned, though the project facilitates collaboration between small and large companies for exploitation.
The robots are designed to collaborate with human workers, using augmented-reality guidance and safety protocols to support manual labor.
The project period runs from 2024-12-01 to 2028-11-30, indicating that full validation and piloting occur within this window.
The consortium is heavily industry-weighted, with 12 industrial partners (67% of the total 18 partners) and 5 SMEs. This high ratio of commercial entities, combined with 5 research organizations across 8 countries, suggests a strong focus on commercial viability and direct industrial application rather than pure academic research.
Contact NORCE RESEARCH AS in Norway
Contact us to connect with the iBot4CRMs industrial partners for pilot integration.
