DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Yoon, Sung-Eui | - |
dc.contributor.advisor | 윤성의 | - |
dc.contributor.author | Kwon, Youngsun | - |
dc.date.accessioned | 2023-06-23T19:34:36Z | - |
dc.date.available | 2023-06-23T19:34:36Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=996357&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/309257 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 전산학부, 2022.2,[vii, 61 p. :] | - |
dc.description.abstract | Understanding a changing environment is one of the essential elements in autonomous robots and systems. A depth sensor or a LiDAR provides the geometric information of the surroundings as a point cloud. As a fundamental technique for robotics applications such as motion planning and collision avoidance, occupancy mapping techniques from sensor data have been studied for decades. However, updating robust representation with real-time processing speed remains a challenging problem of occupancy mapping in a dynamic environment, since the point cloud data of a single scan contains partial geometry observations of the environment. This dissertation studies the occupancy mapping techniques that update their dense occupancy representations in real-time, exploiting spatial correlation of point cloud data. Specifically, we propose a method for real-time occupancy updates in a dynamic environment | - |
dc.description.abstract | 1) an acceleration algorithm exploiting the geometric update patterns of an occupancy map. Furthermore, we propose two approaches to update the dense occupancy representation of the environment given sparse sensor data | - |
dc.description.abstract | 2) regression method using correlation among occupancy observations, and 3) deep-learning network embedding prior knowledge about the spatial correlation of measuring sensor data. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.title | Real-time dense occupancy mapping using spatial correlation of point clouds | - |
dc.title.alternative | 점군 데이터의 공간 상관성을 활용한 실시간 정밀 점유 지도 생성 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | 권용선 | - |
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