CASIA OpenIR  > 多模态人工智能系统全国重点实验室  > 三维可视计算
Visual Reconstruction and Localization-Based Robust Robotic 6-DoF Grasping in the Wild
Liang, Ji1,2; Zhang, Jiguang3; Pan, Bingbing1,3; Xu, Shibiao1,3; Zhao, Guangheng1,2; Yu, Ge2; Zhang, Xiaopeng1,3
Source PublicationIEEE ACCESS
ISSN2169-3536
2021
Volume9Issue:99Pages:72451-72464
Abstract

The intelligent grasping expects that the manipulator has the ability to grasp objects with high degree of freedom in a wild (unstructured) environment. Due to low perception ability in handing targets and environments, most industrial robots are limited to top-down 4-DoF grasping. In this work, we propose a novel low-cost coarse to fine robotic grasping framework. First, we design a global localization based environment perception method, which enables the manipulator to roughly and automatically locate work space. Then, constrained by the above initial localization, a 3D point cloud reconstruction based 6-DoF pose estimation method is proposed for the manipulator further fine locating grasping target. Finally, our framework realizes full function of visual 6DoF robotic grasping, which includes two different visual servoing and grasp planning strategies for different objects grasping. Meanwhile, it also can integrate various state-of-arts 6DoF pose estimation algorithms to facilitate various practical grasping applications or researches. Experimental results show that our method achieves autonomous robotic grasping with high degree of freedom in an unknown environment. Especially for objects with occlusion, singular shape or small scale, our method can still maintain robust grasping.

KeywordGrasping Three-dimensional displays Manipulators Pose estimation Solid modeling Service robots Feature extraction Robotic grasping manipulator 6-DoF pose estimation point cloud reconstruction
DOI10.1109/ACCESS.2021.3079245
Indexed BySCI
Language英语
Funding ProjectProspective Topic of Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences[Y8031851SY] ; Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences[LSU-KFJJ-2020-04]
Funding OrganizationProspective Topic of Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences ; Open Research Fund of Key Laboratory of Space Utilization, Chinese Academy of Sciences
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000652043100001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Sub direction classification三维视觉
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/44688
Collection多模态人工智能系统全国重点实验室_三维可视计算
Corresponding AuthorPan, Bingbing; Zhao, Guangheng
Affiliation1.Univ Chinese Acad Sci, Technol & Engn Ctr Space Utilizat, Beijing 100864, Peoples R China
2.Chinese Acad Sci, Technol & Engn Ctr Space Utilizat, Key Lab Space Utilizat, Beijing 100094, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Liang, Ji,Zhang, Jiguang,Pan, Bingbing,et al. Visual Reconstruction and Localization-Based Robust Robotic 6-DoF Grasping in the Wild[J]. IEEE ACCESS,2021,9(99):72451-72464.
APA Liang, Ji.,Zhang, Jiguang.,Pan, Bingbing.,Xu, Shibiao.,Zhao, Guangheng.,...&Zhang, Xiaopeng.(2021).Visual Reconstruction and Localization-Based Robust Robotic 6-DoF Grasping in the Wild.IEEE ACCESS,9(99),72451-72464.
MLA Liang, Ji,et al."Visual Reconstruction and Localization-Based Robust Robotic 6-DoF Grasping in the Wild".IEEE ACCESS 9.99(2021):72451-72464.
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