[1]戴福全、刘路杰.基于视觉引导的机器人抓取分类系统设计[J].福建工程学院学报,2020,18(06):530-534.[doi:10.3969/j.issn.1672-4348.2020.06.004]
　DAI Fuquan,LIU Lujie.Design of vision-guided robotic grasping classification system[J].Journal of FuJian University of Technology,2020,18(06):530-534.[doi:10.3969/j.issn.1672-4348.2020.06.004]
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基于视觉引导的机器人抓取分类系统设计()
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《福建工程学院学报》[ISSN:2097-3853/CN:35-1351/Z]

卷:
第18卷
期数:
2020年06期
页码:
530-534
栏目:
出版日期:
2020-12-25

文章信息/Info

Title:
Design of vision-guided robotic grasping classification system
作者:
戴福全、刘路杰
福建工程学院机械与汽车工程学院
Author(s):
DAI Fuquan1; 2;  LIU Lujie
School of Mechanical and Automotive Engineering, Fujian University of Technology
关键词:
机器视觉; 工业机器人; 零件分类; 模板匹配; Halcon
Keywords:
machine vision;  industrial robot;  parts classification;  template matching;  Halcon
分类号:
TH166;TG659
DOI:
10.3969/j.issn.1672-4348.2020.06.004
文献标志码:
A
摘要:
为了解决流水线的快速抓取及分类问题，采用六自由度串联工业机器人和SCARA 四轴机器人结合，配合3D 和2D 相机，搭建了一套智能分类抓取系统。基于Halcon 视觉处理平台，在Qt 软件框架下进行二次开发，构建了机器人视觉引导的自动抓取和分类软件框架。通过相机采集图像，并在上位机中经图像预处理、位姿估计、模板匹配等步骤后，得到三维位姿或中心坐标，并发送给机器人实行智能抓取，从而实现对多种堆叠物块的识别和抓取。实验结果表明，通过视觉定位得到的物块中心位置和机械手实际抓取测量之间的误差为0.05~1.22 mm，摆放角度在5°以内时，分拣效率比人工分拣提高了62%左右，可以更好地满足实际企业生产的需求。
Abstract:
In order to solve the problem of rapid grabbing and classification of the assembly line, the system used a combination of a six-degree-of-freedom tandem industrial robot and a SCARA four-axis robot, together with 3D and 2D cameras, to build an intelligent classification and grasping system. Based on the vision processing platform Halcon, secondary development was carried out under the Qt software framework, and the automatic grasping and classification software framework guided by robot vision was constructed. The system collects images through the camera, and after image preprocessing, pose estimation, template matching and other steps in the host computer, the three-dimensional pose or center coordinates were obtained and sent to the robot for intelligent grasping, thereby realizing the identification and grabbing of several stacked blocks. Experimental results show that the error between the center position of the block obtained by visual positioning and the actual grasping measurement of the manipulator is 0.05~1.22 mm.When the placement angle is within 5°, the sorting efficiency of the robot is increased by about 62% than that of the manipulator. Therefore, it can better meet the requirements of the actual enterprise production.

参考文献/References:

[1] 田闯. 工业机器人的现状及发展趋势研究[J]. 中国管理信息化, 2019, 22(20): 156-157.[2] 叶卉, 张为民, 张欢, 等. 机器人智能抓取系统视觉模块的研究与开发[J]. 组合机床与自动化加工技术, 2016(12): 1-5.[3] 解明利, 胡占齐. 机器视觉在柔性制造生产线分拣机械手中的应用研究[J]. 制造技术与机床, 2018(3): 103-107, 113.[4] 陈立挺, 聂晓根. 基于双目视觉的机械手识别、定位、抓取系统研究[J]. 机电工程, 2019, 36(8): 862-866, 872.[5] 党宏社, 候金良, 强华, 等. 基于视觉引导的SCARA机器人自动装配系统[J]. 电子技术应用, 2017, 43(5): 21-24.[6] 杜召辉, 刘安东. 基于Qt的移动机器人上位机软件设计与实现[J]. 计算机测量与控制, 2018, 26(5): 107-111.[7] 钱振奇, 王战中, 杜小强. 基于HALCON的单目视觉标定研究[J]. 石家庄铁道大学学报(自然科学版), 2018, 31(3): 75-80.[8] 田春林, 陈李博, 马国庆, 等. 基于Halcon的工业机器人手眼标定方法研究[J]. 制造业自动化, 2018, 40(3): 16-18, 46[9] 胡玥红. 基于机器视觉的锂电池极片缺陷检测研究[D]. 哈尔滨: 哈尔滨工业大学, 2015.[10] THORMHLEN T, BROSZIO H. Automatic line-based estimation of radial lens distortion[J]. Integrated Computer-Aided Engineering, 2005, 12(2): 177-190. [11] 白钢华, 李王辉. 基于Qt的TCP Socket通信编程研究[J]. 电脑编程技巧与维护, 2013(24): 52-53, 65.

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更新日期/Last Update: 2020-12-25