Robotic Pick-and-Toss Facilitates Urban Waste Sorting
Fredy Raptopoulos, Maria Koskinopoulou, Michail Maniadakis
Abstract
Incorporating robots into industrial settings is not a new concept, but their use in the waste recycling industry is critical. Recently AI-assisted robots are used to support waste sorting and improve the quantity and quality of recovered materials. This article aims to study and apply a new transfer paradigm for recyclable sorting using Delta robots, which is based on replacing the usual Pick-and-Place process with the much faster Pick-and-Toss process. Current robotic sorting systems can sort one item per second, Pick-and-Toss intends to significantly advance this score. We quantitatively and qualitatively assess the tossing approach by comparing it to Pick-and-Place, in terms of accuracy and robustness, both in simulation and on a real waste sorting lab-setup equipped with an ABB-IRB360 Delta robot. Overall, the Pick-and-Toss approach proves to be a powerful mechanism that succeeds faster sorting of waste streams in comparison to the standard Pick-and-Place procedure.