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

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.