RGB-D Visual Simultaneous Localization and Mapping (SLAM) Application
dc.creator | Wang, Weihan | |
dc.date.accessioned | 2020-08-22T21:14:04Z | |
dc.date.available | 2021-10-17 | |
dc.date.issued | 2019-10-17 | |
dc.identifier.uri | https://etd.library.vanderbilt.edu/etd-10172019-171912 | |
dc.identifier.uri | http://hdl.handle.net/1803/14332 | |
dc.description.abstract | Simultaneous localization and mapping (SLAM), as one of the important techniques for navigation, robotic mapping and odometry, has been paid a lot of attention by both academia and industry. Visual slam, as an important branch of slam, which relies on visual sensors, such as monocular cameras, stereo rigs, RGB-D cameras, for state estimation, may become the next trend of SLAM due to its price advantages than traditional sensors. In this thesis, we propose a visual SLAM algorithm based on RGB-D camera and deploy it on a real race car (F1/10). The experiment results show our algorithm works well for both online dataset and real environment. | |
dc.format.mimetype | application/pdf | |
dc.subject | Racecar | |
dc.subject | SLAM | |
dc.title | RGB-D Visual Simultaneous Localization and Mapping (SLAM) Application | |
dc.type | thesis | |
dc.contributor.committeeMember | Xenofon D. Koutsoukos | |
dc.contributor.committeeMember | Richard Alan Peters | |
dc.type.material | text | |
thesis.degree.name | MS | |
thesis.degree.level | thesis | |
thesis.degree.discipline | Computer Science | |
thesis.degree.grantor | Vanderbilt University | |
local.embargo.terms | 2021-10-17 | |
local.embargo.lift | 2021-10-17 |
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Electronic Theses and Dissertations
Electronic theses and dissertations of masters and doctoral students submitted to the Graduate School.