자료유형 | 학위논문 |
---|---|
서명/저자사항 | Towards Robust Dense Visual Simultaneous Localization and Mapping (SLAM). |
개인저자 | Falquez, Juan M. |
단체저자명 | University of Colorado at Boulder. Computer Science. |
발행사항 | [S.l.]: University of Colorado at Boulder., 2018. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
형태사항 | 128 p. |
기본자료 저록 | Dissertation Abstracts International 80-02B(E). Dissertation Abstract International |
ISBN | 9780438382763 |
학위논문주기 | Thesis (Ph.D.)--University of Colorado at Boulder, 2018. |
일반주기 |
Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B.
Adviser: Christoffer Heckman. |
요약 | Long-term autonomy is the dream of many roboticists -- and if a robotic system can be split into three main categories: perception, planning and control -- then the biggest challenges to achieve this dream are undoubtedly faced in perception. La |
요약 | The objective of this dissertation is to present components that would lead to a robust dense visual SLAM system. It starts by exploring 3D reconstruction algorithms, showing distinctions between local and global methods and presenting an increm |
요약 | It then introduces the concept of sensor fusion, where multiple sensors are joined to provide a higher degree of tracking accuracy. It compares different visual SLAM systems -- dense and semi-dense -- and shows how the inclusion of an Inertial M |
요약 | Finally, it explores different error metrics used in direct photometric optimization -- the foundation of dense tracking systems. It introduces the Normalized Information Distance (NID), an entropy based metric that is shown to achieve high loca |
일반주제명 | Robotics. |
언어 | 영어 |
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