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基于形状先验模型的平面型工件抓取位姿检测

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发表于 2017-9-3 12:34:13 | 只看该作者 回帖奖励 |倒序浏览 |阅读模式
基于形状先验模型的平面型工件抓取位姿检测




基于形状先验模型的平面型工件抓取位姿检测.pdf (998.88 KB, 下载次数: 1)




基于形状先验模型的平面型工件抓取位姿检测
郑晶怡1,2, 李恩1,2, 梁自泽1,2
1. 中国科学院大学,北京 100049;
2. 中国科学院自动化研究所,北京 100190
Grasping Posture Determination of Planar Workpieces Based on Shape Prior Model
ZHENG Jingyi1,2, LI En1,2, LIANG Zize1,2
1. University of Chinese Academy of Sciences, Beijing 100049, China;
2. Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

全文: PDF (999 KB)   HTML (1 KB)  
输出: BibTeX | EndNote (RIS)
摘要 为了能够在复杂的工业环境中抓取平面型工件,提出一种图割法与形状先验模型结合的工件图像分割方法,并且对工件的位姿信息进行测量.首先,建立先验形状,提出基于最小包围矩形法将工件的形状模板与目标工件人工分割形状进行配准,得到先验形状.为了保证分割结果的准确性,采用单一的先验形状.图割模型中加入了目标形状先验知识.其次,通过自适应调整形状先验项的权重系数,使得图割法的能量函数形状先验项自适应于被分割的图像.第三,本文可以采用形状先验方法分割一幅图像中的多个工件,并且能够计算吸盘的最优抓取位置.最后,采用结构光视觉系统采集工件的点云信息,拟合工件平面,确定工件法向量,得到工件的抓取姿态.实验结果表明,本文算法能够适应遮挡、光照变化的工件图像,同时也能够分割复杂环境中的目标工件;平面型工件抓取位姿的计算结果有效,可以应用于遮挡、反光、复杂干扰背景条件下的工件抓取作业.
关键词 工件分割,  形状先验,  抓取位姿,  结构光视觉系统   
Abstract:A new shape prior segmentation method based on graph cuts is used to segment workpiece images and measure the workpiece posture for grasping workpieces in cluttered industry scene. Firstly, a prior shape is built. Minimum bounding rectangle method is proposed to register the workpiece shape model and the manual shape of the target workpiece to get the prior shape. In order to ensure the segmentation accuracy, a single prior shape is used. The target shape prior knowledge is added to the graph cut model. Secondly, the weight of the shape prior term is adjusted in a self-adaptive manner, so that the shape prior term of the energy function in graph cut method becomes adaptive to the image to be segmented. Thirdly, multiple workpieces in a image can be segmented by the shape prior method. Meanwhile, the optimal position of suction cup for grasping the workpiece is determined. Finally, the structured light vision system is used to acquire the point cloud of the workpiece. The plane of the workpiece is fitted and the normal vector is determined. Thus, the grasping orientation is obtained. The effectiveness of the proposed approach is demonstrated on the workpiece segmentation in the scene with occlusion, light variation and cluttered background. The posture of the planar workpiece acquired through calculation is accurate, and can be applied to the grasping operation in conditions of occlusion, reflection and complicated background.
Key wordsworkpiece segmentation           shape prior           grasp posture           structured light vision system
收稿日期: 2016-07-22     
1:
TP24
基金资助:国家863计划(2013AA041002-1);国家科技支撑计划(2015BAK06B01);国家自然科学基金(61403372,61403374)
通讯作者: 郑晶怡,jingyi.zheng@ia.ac.cn    E-mail: jingyi.zheng@ia.ac.cn
作者简介: 郑晶怡(1987-),女,博士.研究领域:机器人视觉,机器人路径规划.
李恩(1979-),男,博士,研究员.研究领域:机器人系统,传感器技术,嵌入式系统.
梁自泽(1963-),男,硕士,研究员.研究领域:先进机器人,智能控制,传感器网络.
引用本文:   
郑晶怡, 李恩, 梁自泽. 基于形状先验模型的平面型工件抓取位姿检测[J]. 机器人, 2017, 39(1): 99-110.        
ZHENG Jingyi, LI En, LIANG Zize. Grasping Posture Determination of Planar Workpieces Based on Shape Prior Model. ROBOT, 2017, 39(1): 99-110.
链接本文:  
http://robot.sia.cn/CN/10.13973/j.cnki.robot.2017.0099         http://robot.sia.cn/CN/Y2017/V39/I1/99


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