Title | GraspGPT: Leveraging Semantic Knowledge From a Large Language Model for Task-Oriented Grasping |
Author | |
Publication Years | 2023-11
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DOI | |
Source Title | |
ISSN | 2377-3774
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Volume | 8Issue:11Pages:7551-7558 |
Keywords | |
URL | [Source Record] |
Indexed By | |
SUSTech Authorship | First
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WOS Accession No | WOS:001089173600011
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Data Source | IEEE
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PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10265134 |
Citation statistics |
Cited Times [WOS]:0
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/575775 |
Affiliation | 1.Shenzhen Key Laboratory of Robotics and Computer Vision, Southern University of Science and Technology, Shenzhen, China 2.Institute for Robotics and Intelligent Machines, Georgia Institute of Technology, Atlanta, GA, USA |
First Author Affilication | Southern University of Science and Technology |
First Author's First Affilication | Southern University of Science and Technology |
Recommended Citation GB/T 7714 |
Chao Tang,Dehao Huang,Wenqi Ge,et al. GraspGPT: Leveraging Semantic Knowledge From a Large Language Model for Task-Oriented Grasping[J]. IEEE Robotics and Automation Letters,2023,8(11):7551-7558.
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APA |
Chao Tang,Dehao Huang,Wenqi Ge,Weiyu Liu,&Hong Zhang.(2023).GraspGPT: Leveraging Semantic Knowledge From a Large Language Model for Task-Oriented Grasping.IEEE Robotics and Automation Letters,8(11),7551-7558.
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MLA |
Chao Tang,et al."GraspGPT: Leveraging Semantic Knowledge From a Large Language Model for Task-Oriented Grasping".IEEE Robotics and Automation Letters 8.11(2023):7551-7558.
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