| 基于YOLOv5s-T和RGB-D相机的螺栓检测与定位系统 |
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| 引用本文： | 王向周,杨敏巍,郑戍华,梅云鹏.基于YOLOv5s-T和RGB-D相机的螺栓检测与定位系统[J].北京理工大学学报,2022,42(11):1159-1166. |
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| 作者姓名： | 王向周 杨敏巍 郑戍华 梅云鹏 |
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| 作者单位： | 北京理工大学 自动化学院，北京 100081 |
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| 基金项目： | 国家电网有限公司总部科技项目“角钢塔塔身螺栓紧固机器人研究”资助（5200-2020036147A-0-0-00） |
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| 摘 要： | 机器人替代人工紧固角钢塔螺栓是解决高空作业安全问题的途径之一. 针对角钢塔螺栓紧固机器人的作业需求，提出了一种基于神经网络和RGB-D相机的角钢塔主材螺栓检测与定位系统，将轻量化的YOLOv5s-T网络应用于英特尔?实感?深度摄像头D435i采集的图像，实现了角钢塔主材螺栓的实时检测、三维定位及重新排序等功能. 经实验验证，YOLOv5s-T在基本不降低均值平均精度（mean average precision，mAP）的情况下，推理速度提高约31%；用RGB-D相机测得的三维坐标计算相邻螺栓间距，平均误差小于1 mm. 对主材螺栓排序算法进行验证，RGB-D相机正对螺栓组模板时，模板的正确排序率不低于95%，可快速引导6自由度机械臂末端到达螺栓紧固点.
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| 关 键 词： | YOLOv5s-T 螺栓检测 三维定位 排序 |
| 收稿时间： | 2021-12-03 |
Bolt Detection and Positioning System Based on YOLOv5s-T and RGB-D Camera |
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| Affiliation: | School of Automation, Beijing Institute of Technology, Beijing 100081, China |
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| Abstract: | Replacing manual works with robots is a feasible solution for solving the safety problem of fastening bolts on the angle steel tower. In order to meet the operating requirements of the angle steel tower bolt fastening robot, a detecting and positioning system was proposed based on neural network and RGB-D camera for the main bolts of the angle steel tower. Applying the lightweight YOLOv5s-T network to the image of the Intel? RealSense? depth camera D435i, the system was used to realize real-time detection, three-dimensional positioning and reordering the main bolts of the angle steel tower. Experiments show that YOLOv5s-T can improve the inference speed of the original algorithm by about 31% without reducing mAP (mean average precision) basically. Using three-dimensional coordinates measured by the RGB-D camera to calculate the distance between adjacent bolts, the average distance error is less than 1 mm. When the RGB-D camera is facing the bolt group template, the correct sorting rate of the template is above 95%. It can guide the end-effector of the 6-dof manipulator toward the target bolt within a short time. |
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