Development of an automatic sorting robot for construction and demolition waste
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ORIGINAL PAPER
Development of an automatic sorting robot for construction and demolition waste Wen Xiao1 · Jianhong Yang1 · Huaiying Fang1 · Jiangteng Zhuang1 · Yuedong Ku1 · Xiaojun Zhang2 Received: 8 January 2020 / Accepted: 11 August 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract An automatic sorting robot is designed in this report. The system makes use of height maps and near-infrared (NIR) hyperspectral images to locate the ROI of objects and to do online statistic pixel-based classification in contours. This approach has two advantages: (1) to generate training data for sorting without manual work; (2) to get more stable final result. Two kind of features in hyperspectral image were extracted, a scale-sensitive algorithm was used to identify amplitude feature and a scale-insensitive algorithm was used to identify trend feature. After location and classification, the robot grabs valuable targets based on their position and posture and places them into the corresponding recycling area based on their category. The prototype machine can automatically sort construction and demolition waste (C&DW) with a size range of 0.05–0.5 m. The sorting efficiency can reach 2028 picks/h, and the online recognition accuracy nearly reaches 100%.
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10098-020-01922-y) contains supplementary material, which is available to authorized users. * Jianhong Yang [email protected] 1
College of Mechanical Engineering and Automation, Huaqiao University, Xiamen, Fujian Province, China
Fujian South Highway Machinery Co., Ltd, Quanzhou, Fujian Province, China
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Graphic abstract
Keywords Construction and demolition waste sorting · Automatic sorting robot · Height map detection · Hyperspectral image classification
Introduction Construction and demolition waste (C&DW) production is increasing. Its uncontrolled generation and disposal negatively impact the environment, and thus research on methods that can recycle C&DW is becoming increasingly important. In China, C&DW production accounts for 30–40% of total waste production. Currently, the vast majority of C&DW is dumped, with an average recycling rate of only about 5% (Huang et al. 2018).
Traditional methods to process C&DW Traditional methods of C&DW treatment cannot keep up with the pace of waste production today, and thus new treatment methods are required. In the traditional methods, C&DW must first be crushed several times, which is a prerequisite step for all subsequent processing (Chen and He 2018). After multiple mechanical screenings, the C&DW is manually sorted by hand, especially in low-income countries (Cesetti and Nicolosi 2016). This traditional type of
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processing is complicated, inefficient, and expensive. Some C&DW can be effectively separated using methods based on a mechanism measuring density or magnetism (Ulsen et al. 2013). However, materials that are able to be sorted using such metho
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