基于人工智能的缝料自动化抓取方法研究  

Research on automatic picking method of sewing materials based on artificial intelligence

作　　者：王光明 徐修亮 WANG Guangming;XU Xiuliang(Hikari(shanghai)Precise Machinery Science&Technology Co,Ltd,Shanghai 201599,China)

机构地区：[1]上海富山精密机械科技有限公司,上海201599

出　　处：《中外缝制设备》2023年第9期73-75,共3页SINO-FOREIGN SEWING MACHINERY

摘　　要：随着工业自动化的快速发展,缝料自动化抓取在缝制行业中具有重要的应用价值。本研究旨在探索基于人工智能的缝料自动化抓取方法,提高缝料自动化生产线的效率和稳定性。首先,我们对缝料的特性进行了分析和分类,以便更好地理解其形态和结构。其次,我们提出了一种基于深度学习的缝料检测算法,通过训练神经网络模型,实现对不同类型缝料的准确识别和定位。再次,我们设计并实现了一种基于机器视觉的缝料抓取系统,结合深度学习模型和机械臂控制算法,实现对缝料的自动化抓取和放置。最后,我们进行了一系列实验验证了所提方法的有效性和稳定性。实验结果表明,该方法能够实现高精度的缝料自动化抓取,并具有较高的鲁棒性和适应性。With the rapid development of industrial automation,automated grabbing of fabrics has significant application value in the textile industry.This study aims to explore AI-based automated grabbing methods for fabrics to improve the efficiency and stability of fabric production lines.Firstly,we analyze and classify the characteristics of fabrics to better understand their morphology and structure.Secondly,we propose a deep learning-based fabric detection algorithm to accurately identify and locate different types of fabrics through training neural network models.Next,we design and implement a machine vision-based fabric grabbing system,combining deep learning models and robotic arm control algorithms,to achieve automated grabbing and placement of fabrics.Finally,a series of experiments are conducted to validate the effectiveness and stability of the proposed methods.The experimental results demonstrate that the proposed method can achieve high-precision automated grabbing of fabrics with high robustness and adaptability.

关 键 词：缝料自动化 深度学习 机器视觉 抓取方法 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]