面向布线机器人的柔性线束识别方法  

Flexible wire harness recognition for wiring robots

作　　者：尚玉玲[1] 刘德璋 刘陶荣 SHANG Yuling;LIU Dezhang;LIU Taorong(School of Electronic and Automation,Guilin University of Electronic Technology,Guilin Guangxi 541004,China)

机构地区：[1]桂林电子科技大学电子工程与自动化学院,广西桂林541004

出　　处：《激光杂志》2024年第11期77-84,共8页Laser Journal

基　　金：国家自然科学基金(No.62364005);桂林电子科技大学研究生创新项目(No.2023YCXS128、2023YCXS117)。

摘　　要：针对当前布线自动化生产过程中没有适用的柔性线束识别方法的问题,提出了一种面向布线机器人的柔性线束识别方法。首先,以UNet网络结构为基础,采用ResNet-34作为编码器中的特征提取网络,并在解码器部分引入SE注意力模块,构建了一个新的图像分割模型RS-UNet,用于线束图像的分割。接着,采用Zhang-Suen图像细化算法,细化线束掩模图像,最后获取线束的几何中心位置信息,给布线机器人操作线束提供引导。通过实验证明,相较于UNet网络,RS-UNet网络在线束分割精度上IoU值提高了4.95%,F1值提高了0.029,并且选用的Zhang-Suen细化算法的平均处理时间为0.38 s,图像细化结果的平均细化敏感度为0.39,平均厚度参考值为0.87,提出的方法可以准确地识别柔性线束的几何中心。Aiming at the problem that there is no applicable flexible wire harness recognition method in the current wiring automation production process,a flexible wire harness recognition method for wiring robots is proposed.Firstly,based on the UNet network structure,ResNet-34 is adopted as the feature extraction network in the encoder,and the SE attention module is introduced in the decoder part to construct a new image segmentation model RS-UNet for the segmentation of wire harness images.Then,the Zhang-Suen image refinement algorithm is used to refine the wire harness mask image,and finally the geometric center position information of the wire harness is obtained to give guidance to the wiring robot to operate the wire harness.Through experiments,it is proved that the RS-UNet network improves the IoU value by 4.95%and the F1 value by 0.029 in the wire harness segmentation accuracy compared to the when-UNet network,and the selected Zhang-Suen refinement algorithm has an average processing time of 0.38 s,an average refinement sensitivity of the image refinement result of 0.39,and an average thickness reference value of 0.87,the proposed method can accurately identify the geometric center of the flexible wire harness.

关 键 词：布线机器人 UNet结构 ResNet特征提取 SE注意力机制 图像细化 

分 类 号：TN249[电子电信—物理电子学]