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ImprovinG waste management through an AI-powered detection system of batteries utilising data from X-Ray detectors and pick-and-place robots.

Project description

AI-based robotic system for electronic waste detection

The management chain for waste from electrical and electronic equipment (WEEE) can cause fire incidences due to batteries carelessly discarded into recycling bins or black rubbish bags. Consequently, this threatens human life, disrupts waste services, and causes considerable economic loss. The EU-funded Grinner project proposes an autonomous AI-enabled robotic sorting system that detects and removes WEEE. The system will consist of the fastest energy-resolved X-Ray detectors on the market and an ML-enabled software module. Grinner will analyse X-ray data, effectively detecting waste containing batteries, and inform the waste flow and vision-based pick-and-place robots. The project will prepare the system for commercialisation.


The WEEE (waste from electrical and electronic equipment) management chain has realised an explosion of fire incidences, caused by carelessly discarded batteries into either recycling bins or black rubbish bags, where they are easily damaged by sorting equipment and start to burn, endangering human lives, disrupting waste services and causing millions of Euros of damage (from €190,000 up to €1.3m per fire incident).

The Grinner project aims at commercialising an autonomous AI-enabled robotic sorting system capable of detecting and removing waste containing batteries from current waste streams before they enter inhospitable-to-battery machines that crush and consolidate waste. The system will comprise (i) the fastest Energy-resolved X-Ray detectors in the market, (ii) an ML-enabled software module that will analyse X-Ray data and effectively detect waste containing batteries while passing through the waste flow and vision-based pick-and-place robot(s) that will remove the flagged WEEE.

Project objectives:
• Build an X-Ray data set of WEEE scrap.
• Customisation of the X-Ray system
• Develop the AI software module for detection of batteries within WEEE using X-Ray data.
• Deploy a vision-based robotic solution capable of Picking-and-Placing WEEE
• Develop, integrate and install a prototype system in a WEEE facility environment to conduct live trials and validate Grinner.
• Explore the potential exploitation of Grinner as an economically viable, stand-alone product for recycling facilities.



Net EU contribution
€ 459 375,00
Ul. ksiecia jozefa poniatowskiego 8
35-026 Rzeszow

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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Makroregion wschodni Podkarpackie Rzeszowski
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Other funding
€ 196 875,00

Participants (5)

Partners (1)