基于特征包的钢筋粘结状态识别

Yunfei Shi, Shitao Liu, Gongzheng Chen, Yupo Pan, Lifang Han, Pengfei Wang
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引用次数: 0

摘要

钢筋捆扎机器人是一种典型的施工机器人,在标准环境下代替人工捆扎钢筋。为了验证基于feature Bag的钢筋绑定状态识别方法对机器人运行过程中采集的绑定图像的有效性,我们开发了机器人原型并搭建了实验环境。该方法成功地对不同光照条件下钢筋的粘结状态和未粘结状态进行了分类,为工程应用提供了指导。文章中使用的数据集已经公开发布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recognition of the rebar binding state based on Bag of Features
Rebar binding robot is a typical kind of construction robot, replacing manual binding of steel bars in a standard environment. We develop a robot prototype and build an experimental environment to verify the effectiveness of the Bag of Features based rebar binding state recognition for the binding images taken during the operation of the robot. The method successfully classifies two states of bound and unbound of rebar under different lighting conditions, providing guidance for the engineering application. The dataset used in the article has been publicly released.
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