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https://scholarbank.nus.edu.sg/handle/10635/36158
DC Field | Value | |
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dc.title | Path Planning, Mapping & Learning for Mobile Robot Navigation | |
dc.contributor.author | ZHANG QUN | |
dc.date.accessioned | 2013-01-31T18:02:02Z | |
dc.date.available | 2013-01-31T18:02:02Z | |
dc.date.issued | 2012-08-23 | |
dc.identifier.citation | ZHANG QUN (2012-08-23). Path Planning, Mapping & Learning for Mobile Robot Navigation. ScholarBank@NUS Repository. | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/36158 | |
dc.description.abstract | Autonomous navigation is the fundamental requirement for mobile robot, which has received considerable attention in recent decades. The main objective of this thesis is to explore the advanced methodologies and techniques for the sensor-based mobile robot navigation and the associated technical issues. It includes (i) Simultaneous Path Planning And Topological Mapping (SP2ATM) for goal oriented navigation and exploration in unknown environments by concurrently extracting Admissible Free Spaces and incrementally constructing a topological map, (ii) Vision-augmented Simultaneous Path Planning And Topological Mapping (V-SP2ATM) for visual localization in 3D environment by integrating stereo vision and laser range finder and optimizing a concurrently constructed pose graph, and (iii) non-metric navigation for intelligent navigation in indoor environments by imitating human learning and navigational behaviors, where the Topo-Semantic Representation is constructed to represent the visual information of the environment and the topological relation between semantic places. | |
dc.language.iso | en | |
dc.subject | Path Planning, Mapping, Learning, Mobile Robot Navigation | |
dc.type | Thesis | |
dc.contributor.department | NUS GRAD SCH FOR INTEGRATIVE SCI & ENGG | |
dc.contributor.supervisor | GE SHUZHI | |
dc.description.degree | Ph.D | |
dc.description.degreeconferred | DOCTOR OF PHILOSOPHY | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Ph.D Theses (Open) |
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ZhangQ.pdf | 22.35 MB | Adobe PDF | OPEN | None | View/Download |
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