Researchers Develop AI-Based Textile Recycling System

A research team at Rochester Institute of Technology’s (RIT) Golisano Institute for Sustainability (GIS) is developing a fully automated system to identify, sort, and disassemble garments at high speed and in high volume, for textile recycling in efforts to address a critical global waste problem.

Led by program manager Mark Walluk, the team, consisting of staff engineers Ryan Parsons ’17 (mechanical engineering), Nick Spears ’24 (robotics and manufacturing engineering technology), Sri Priya Das, Ronald Holding and Christopher Piggot ’91 (computer engineering and technology), as well as associate research professor Abu Islam, is using an automated system to detect and remove these non-recyclable elements to enable higher-value material recovery.

Senior Staff Mechanical Engineer Ryan Parsons, right, calibrates a laser safety tube for an AI-guided robotic arm while associate research professor Abu Islam, back left, oversees the performance. The machine uses machine learning and laser technology to identify and remove non-recyclable material. Carlos Ortiz/RIT

The process begins with a conveyor-fed imaging station where three specialized cameras generate a high-resolution, multi-dimensional map of the garment which allows for fiber composition analysis down to the millimeter level. The system then leverages artificial intelligence and machine vision to identify and remove non-recyclable elements from clothing, which proved to be a unique challenge for the team.

Though still in the pilot phase, the technology is already attracting interest globally from recyclers in the U.S., Europe, South Asia, and Latin America. The team anticipates transitioning the system to its partners for continued testing and potential deployment later this year. www.rit.edu