Optimizing Waste Sorting for Sustainability: An AI-Powered Robotic Solution for Beverage Container Recycling.

With Japan facing workforce shortages and the need for enhanced recycling systems due to an aging population and increasing environmental challenges, automation in recycling facilities has become a key component for advancing sustainability goals. This study presents the development of an automated sorting robot to replace manual processes in beverage container recycling, aiming to address environmental, social, and economic sustainability by optimizing resource efficiency and reducing labor demands. Using artificial intelligence (AI) for image recognition and high-speed suction-based grippers, the robot effectively sorts various container types, including PET bottles and clear and colored glass bottles, demonstrating a pathway toward more sustainable waste management practices. The findings indicate that stabilizing items on the sorting line may enhance acquisition success, although clear container detection remains an AI challenge. This research supports the United Nation's 2030 Agenda for Sustainable Development by advancing recycling technology to improve waste processing efficiency, thus contributing to reduced pollution, resource conservation, and a sustainable recycling infrastructure. Further development of gripper designs to handle deformed or liquid-containing containers is required to enhance the system's overall sustainability impact in the recycling sector. [ABSTRACT FROM AUTHOR]