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https://hdl.handle.net/10356/46783
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Reeti Burman | en_US |
dc.date.accessioned | 2011-12-23T09:53:13Z | |
dc.date.available | 2011-12-23T09:53:13Z | |
dc.date.copyright | 2010 | en_US |
dc.date.issued | 2010 | |
dc.identifier.uri | http://hdl.handle.net/10356/46783 | |
dc.description | 51 p. | en_US |
dc.description.abstract | This thesis presents a solution to Simultaneous Localization and Mapping (SLAM) problem, which comprises of two tasks to be done simultaneously, that is, localizing robot's pose and building up a map, using data generated from scan-matching algorithm as estimated odometry data. An Extended Kalman filter approach is used to process the scan-matching data obtained from the information acquired from die laser scanner mounted on the robot. | en_US |
dc.rights | Nanyang Technological University | en_US |
dc.subject | DRNTU::Engineering::Electrical and electronic engineering | en_US |
dc.title | EKF based simultaneous localization and mapping | en_US |
dc.type | Thesis | en_US |
dc.contributor.supervisor | Wang Han | en_US |
dc.contributor.school | School of Electrical and Electronic Engineering | en_US |
dc.description.degree | Master of Science (Computer Control and Automation) | en_US |
item.fulltext | With Fulltext | - |
item.grantfulltext | restricted | - |
Appears in Collections: | EEE Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
EEE_THESES_130.pdf Restricted Access | 3.71 MB | Adobe PDF | View/Open |
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