A pose estimation system based on deep neural network and ICP registration for robotic spray painting application
文献类型：期刊论文
| 作者 | Wang, Zhe1,2 ; Fan, Junfeng1,2; Jing, Fengshui1,2; Liu, Zhaoyang1,2; Tan, Min1,2
|
| 刊名 | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
 |
| 出版日期 | 2019-09-01 |
| 卷号 | 104期号:1-4页码:285-299 |
| 关键词 | Pose estimation Spray painting RGB-D sensor Deep neural network ICP registration |
| ISSN号 | 0268-3768 |
| DOI | 10.1007/s00170-019-03901-0 |
| 通讯作者 | Jing, Fengshui(fengshui.jing@ia.ac.cn) |
| 英文摘要 | Nowadays, off-line robot trajectory generation methods based on pre-scanned target model are highly desirable for robotic spray painting application. For actual implementation of the generated trajectory, the relative pose between the actual target and the model needs to be calibrated in the first place. However, obtaining this relative pose remains a challenge, especially from a safe distance in industrial setting. In this paper, a pose estimation system that is able to meet the robotic spray painting requirements is proposed to estimate the pose accurately. The system captures the image of the target using RGB-D vision sensor. The image is then segmented using a modified U-SegNet segmentation network and the resulting segmentation is registered with the pre-scanned model candidates using iterative closest point (ICP) registration to obtain the estimated pose. To strengthen the robustness, a deep convolutional neural network is proposed to determine the rough orientation of the target and guide the selection of model candidates accordingly thus preventing misalignment during registration. The experimental results are compared with relevant researches and validate the accuracy and effectiveness of the proposed system. |
| WOS关键词 | RECOGNITION ; TOOL |
| 资助项目 | National Natural Science Foundation of China[U1813208] ; National Natural Science Foundation of China[61573358] |
| WOS研究方向 | Automation & Control Systems ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000483808200016 |
| 出版者 | SPRINGER LONDON LTD |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/27217]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 |
| 通讯作者 | Jing, Fengshui |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Zhe,Fan, Junfeng,Jing, Fengshui,et al. A pose estimation system based on deep neural network and ICP registration for robotic spray painting application[J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,2019,104(1-4):285-299. |
| APA | Wang, Zhe,Fan, Junfeng,Jing, Fengshui,Liu, Zhaoyang,&Tan, Min.(2019).A pose estimation system based on deep neural network and ICP registration for robotic spray painting application.INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY,104(1-4),285-299. |
| MLA | Wang, Zhe,et al."A pose estimation system based on deep neural network and ICP registration for robotic spray painting application".INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 104.1-4(2019):285-299. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。