期刊
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
卷 10, 期 2, 页码 362-373出版社
INST CONTROL ROBOTICS & SYSTEMS, KOREAN INST ELECTRICAL ENGINEERS
DOI: 10.1007/s12555-012-0216-9
关键词
Bin-picking; industrial robot; robot vision; stereo vision
资金
- MKE, Korea [NIPA-2012-(C1090-1221-0008)]
- NRF / MEST, Korea [R31-10062-0, 2011-0018397]
- Korea Evaluation Institute of Industrial Technology (KEIT) [10033412, 4-1] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- Ministry of Public Safety & Security (MPSS), Republic of Korea [H0301-12-3001] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
- National Research Foundation of Korea [2010-0020210, 과C6A1605] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
As flexibility becomes an important factor in factory automation, the bin-picking system, where a robot performs pick-and-place tasks for randomly piled parts in a bin through measuring the 3D pose of an object by a 3D vision sensor, has been actively studied. However, conventional bin-picking systems that are employed for particular tasks are limited by such things as the FOV (Field of View), the shape of landmark features, and computation time. This paper proposes a general-purpose stereo vision based bin-picking system. To detect the workpiece to be picked, a geometric pattern matching (GPM) method with respect to the 2D image with a wide FOV is applied. The accurate 3D pose of a selected workpiece among the pick-up candidates is acquired by measuring the 3D positions of three features in the workpiece using the stereo camera. In order to improve the 3D position estimation performance, the GPM method is also used instead of the stereo matching method. The multiple pattern registration and ellipse fitting techniques are additionally applied to increase the reliability. The grasp position of a workpiece without collision is determined using the pose of the object and the bin information. By using these methods a practical bin-picking strategy is established to operate robustly with minimum help from the human workers in the factory. Through experiments on commercial industrial workpieces and industrial robot, we validated that the proposed vision system accurately measures the 3D pose of part and the robot successfully manipulates the workpiece among randomly stacked parts.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据