L2M – AI-powered Vision-based Robotic System for Autonomous Waste Sorting and Recycling

Waste sorting today is inefficient and relatively expensive since current systems can’t achieve full autonomy. Our project introduces a practical solution that combines AI-powered vision-based object detection with low-cost robotic manipulators to automatically detect and sort waste streams in real time. This innovation reduces hardware and maintenance costs, minimizes the labor reliance, and greatly enhances the overall efficiency. By embedding robotics and AI into waste processing, we deliver a reliable and economically accessible recycling approach that promotes the circular economy and reduce landfill dependency.

Faculty Supervisor:

Ting Zou

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Engineering

Sector:

Artificial Intelligence; Clean Technology; Environmental Science and Technology

University:

Memorial University of Newfoundland

Program: