DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Jo, Sungho | - |
dc.contributor.advisor | 조성호 | - |
dc.contributor.author | Kwak, Ji Ho | - |
dc.date.accessioned | 2023-06-26T19:31:42Z | - |
dc.date.available | 2023-06-26T19:31:42Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1032958&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/309574 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학부, 2023.2,[iii, 19 p. :] | - |
dc.description.abstract | In this paper, we studied semantic grasping for robotic manipulation. For efficient robotic manipulation, the robot should change the grasping position, grasping force, and gripper type depending on the object's material, characteristics, and purpose of grasping. However, designating characteristics and grasping parameters for every object is inconvenient and inefficient. To solve this problem, we suggest a method to predict appropriate grasping parameters for objects whose grasping parameters are unknown. We show that grasping parameters can be predicted using the knowledge graph embedding method over the knowledge graph of objects' characteristics, their relation, and grasping parameters. Furthermore, we developed a method for a robot to decide the appropriate grasping parameter by collecting information about an object using its recognition module. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | AI-enabled robotics▼agrasping▼arepresentation learning | - |
dc.subject | 지능 로봇▼a로봇 파지▼a표현학습 | - |
dc.title | Semantic grasping for robotic manipulation through knowledge graph | - |
dc.title.alternative | 지식 그래프를 활용한 로봇의 의미론적 파지법에 대한 연구 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | 곽지호 | - |
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