FEIT Research Project Database

Developing AI enabled vision for plastic waste identification and autonomous robotic sorting

Project Leader: Shanaka Kristombu Baduge
Staff: Dr Eric Schoof, Prof Priyan Mendis, Prof Shanika Karunasekara
Collaborators: Advanced Circular Polymers
Sponsors: Department of Industry Science Energy and Resources CRC-P CRCPX000010
Primary Contact: Kasun Shanaka Kristombu Baduge (kasun.kristombu@unimelb.edu.au)
Keywords: Algorithms; artificial intelligence; deep learning; machine learning
Disciplines: Computing and Information Systems,Electrical & Electronic Engineering,Infrastructure Engineering

Since many foreign countries have restricted the importing of waste, the Australian Government has set a target to ban the export of waste by 2021 and achieve a 80% resource recovery rate by 2030. However, the generation of substantial amount of no-value plastic residue in recycling plants due to inefficient sorting systems results in unprofitable landfill cost while reducing the overall plant material recovery rate and profitability.

This project is aimed at developing state-of-the-art deep learning algorithms to assist in autonomous sorting of plastic waste using robotic systems. Successful candidates will have a very good exposure to an industry-oriented project with an opportunity to build skills in Artificial Intelligence, Deep Learning, Robotic Systems, Sustainability and Circular Economy.

The project is a collaboration with Department of Electrical and Electronic Engineering and School of Computing and Information Systems.

Further information: https://business.gov.au/grants-and-programs/cooperative-research-centres-projects-crcp-grants/crc-projects-selection-round-outcomes