基于LabVIEW的螺钉柔性抓取关键技术研究
Research on Key Technology of Screw Flexible Grasping Based on LabVIEW
段怡 1刘超2
作者信息
- 1. 重庆建筑科技职业学院数字工程学院,重庆 401331
- 2. 贵州习酒股份有限公司,贵州习水 564622
- 折叠
摘要
为了解决某系列非标螺钉的自动上料问题,提出了基于机器视觉的螺钉柔性抓取系统.首先设计了Eye-to-hand视觉定位抓取系统,对采集的图像进行二值化、粒子分析等图像预处理识别螺钉目标.其次,针对螺钉目标采用拟合圆操作获取螺钉中心方向的系列圆特征参数,通过最小二乘法拟合求得中心线,进一步求解螺钉的抓取点与角度位姿参数.最后,以抓取点为中心设计符合夹爪抓取特性的ROI区域以判断可抓性.上位机将位姿信息发送到控制器,引导机器人运动到相应位置并通过末端夹爪完成对螺钉工件的抓取.通过实验验证表明系统定位准确率达到99.5%.
Abstract
In order to solve the automatic feeding problem of a series of non-standard screws,a screw flexible grasping system based on machine vision was proposed.Firstly,the Eye-to-hand visual positioning and grasping system was designed,and the ac-quired images were identified by image preprocessing such as binarization and particle analysis.Secondly,for the screw target,a series of circular characteristic parameters of the screw center direction were obtained by fitting the circle operation,and the cen-ter line was obtained by fitting the least square method,furthermore,pose parameters of grasping point and angle of the screw were solved.Finally,the ROI region conforming to the grasping characteristics of the claw was designed with the grasping point as the center to judge the grasping.The upper computer sent the pose information to the controller,guided the robot to move to the corre-sponding position,and completed the grasping of the screw workpiece through the end claw.Through the experimental verifica-tion,the positioning accuracy of the system is 99.5%.
关键词
机器视觉/定位引导/柔性抓取/图像处理/螺钉/最小二乘法Key words
machine vision/positioning and guidance/flexible grasping/image processing/screw/least square method引用本文复制引用
基金项目
国家重点研发专项(2020YFB1710500)
出版年
2023
NETL
NSTL
维普
万方数据