Workpiece Identification and Localization Based on Monocular
文献类型：会议论文
| 作者 | Guan Y(管宇)1,2,3 ; Tian JD(田建东)2,3; Tang YD(唐延东)2,3
|
| 出版日期 | 2019 |
| 会议日期 | July 29 - August 2, 2019 |
| 会议地点 | Suzhou, China |
| 页码 | 1612-1616 |
| 英文摘要 | In this paper, based on monocular vision, a workpiece positioning method is proposed for solving the workpiece grabbing program on the planar workbench of industrial assembly line. When an object has large affine deformations, contour information based methods may fail to estimate the object position. To solve this problem, we first use affine-scale invariant feature transform (A-SIFT) method to find the coarse matched feature points between the measured workpiece and the planned one. Then, a criterion is established to evaluate the matching accuracy of these coarse matched feature points. Finally, we select a well-matched subset from the coarse matched ones to calculate displacement and rotation angles between the measured workpiece and the planned one. Experimental results show that this method handles well for various workpieces with different shapes and achieves high matching accuracy. Especially, it is also applicable for large affine changes under different industrial scenes. |
| 产权排序 | 1 |
| 会议录 | Proceedings of 9th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems
 |
| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-0769-1 |
| WOS记录号 | WOS:000569550300283 |
| 源URL | [http://ir.sia.cn/handle/173321/27176]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 通讯作者 | Guan Y(管宇) |
| 作者单位 | 1.University of Chinese Academy of Sciences, Beijing 100049, China 2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang 110016, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China |
| 推荐引用方式 GB/T 7714 | Guan Y,Tian JD,Tang YD. Workpiece Identification and Localization Based on Monocular[C]. 见:. Suzhou, China. July 29 - August 2, 2019. |
入库方式： OAI收割
来源：沈阳自动化研究所
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