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基于TOF相机的备煤仓清理识别定位方法

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在传统制造业致力于自动化、智能化升级的时代背景下,针对钢铁行业备煤仓异物清理过程中生产环境复杂、工作周期长、危险性高等特点,提出一种基于TOF相机的备煤仓清理识别定位方法.首先使用TOF相机获取备煤仓下料口深度图像并将其投影为二维图像;其次使用预处理算法对图像进行增强处理得到清晰二值化图像;然后利用斑点检测计算落料口栏杆间隙中心坐标;进而计算异物中心点所在间隙坐标实现异物定位.最后通过实验证明该方法能够准确识别下料口处异物的位置,引导机器人完成对多种异物的抓取清理工作.
Method of Cleaning Identification and Positioning of Coal Bunker Based on TOF Camera
In the context of the traditional manufacturing industry's commitment to automation and intelligent upgrading,a TOF camera based method for identifying and locating foreign objects in the preparation coal bin cleaning process in the steel industry is proposed to address the complex production environment,long work cycles,and high risks involved.Firstly,the TOF camera is used to obtain the depth image of the coal preparation bin discharge port and project the depth image into a two-dimensional image.Secondly,use preprocessing algorithms to enhance the image and obtain clear binary images.Then use spot detection to calculate the center coordinates of the gap between the material discharge port railing.Further calculate the gap coordinates of the center point of the foreign object to achieve foreign object localization.Finally,experiments have shown that this method can accurately identify the position of foreign objects at the feeding port,guiding the robot to complete the grasping and cleaning of various foreign objects.

Machine visionTOF camera3D imaging technologyDepth imageSpot detection

任志墨、张文昌、李贞逸、沈敏举

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北京机科国创轻量化科学研究院有限公司,北京 100083

先进成形技术与装备国家重点实验室,北京 100083

机器视觉 TOF相机 3D成像技术 深度图像 斑点检测

2024

机电产品开发与创新
中国机械工业联合会

机电产品开发与创新

影响因子:0.211
ISSN:1002-6673
年,卷(期):2024.37(5)