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Development of an automatic sorting robot for construction and demolition waste
Clean Technologies and Environmental Policy ( IF 4.3 ) Pub Date : 2020-08-28 , DOI: 10.1007/s10098-020-01922-y
Wen Xiao , Jianhong Yang , Huaiying Fang , Jiangteng Zhuang , Yuedong Ku , Xiaojun Zhang

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%.

Graphic abstract



中文翻译:

开发用于建筑和拆除废物的自动分拣机器人

摘要

此报告中设计了一个自动分拣机器人。该系统利用高度图和近红外(NIR)高光谱图像来定位对象的ROI,并在轮廓中进行基于统计像素的在线分类。这种方法有两个优点:(1)无需手工就可以生成训练数据进行分类。(2)获得更稳定的最终结果。提取了高光谱图像中的两种特征,采用比例敏感算法识别幅度特征,采用比例不敏感算法识别趋势特征。在对位置进行分类之后,机器人会根据它们的位置和姿势来捕获有价值的目标,并根据其类别将它们放入相应的回收区域。原型机可以自动分类大小为0的建筑和拆除废物(C&DW)。05–0.5 m。分拣效率可达2028次/小时,在线识别准确率接近100%。

图形摘要

更新日期:2020-08-28
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