Robotic Pick-and-Toss Facilitates Urban Waste Sorting *

Fredy Raptopoulos, Maria Koskinopoulou, M. Maniadakis
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引用次数: 15

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.
机器人拾取和投掷方便城市垃圾分类*
将机器人融入工业环境并不是一个新概念,但它们在废物回收行业的应用至关重要。最近,人工智能辅助机器人被用于支持垃圾分类,提高回收材料的数量和质量。本文旨在研究和应用Delta机器人对可回收物分类的一种新的转移范式,该范式基于用更快的拾取-丢弃过程取代通常的拾取-放置过程。目前的机器人分拣系统每秒可以分拣一件物品,而Pick-and-Toss计划显著提高这一分数。在模拟和配备了ABB-IRB360 Delta机器人的真实垃圾分类实验室设置中,我们通过将其与拾取-放置进行比较,定量和定性地评估了投掷方法的准确性和鲁棒性。总的来说,与标准的拾取-放置程序相比,拾取-丢弃方法被证明是一种强大的机制,可以更快地对废物流进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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