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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Datta, A. Kin-Choong Yow |
| Copyright Year | 2011 |
| Description | Author affiliation: School of Computer Engineering, Nanyang Technological University, Singapore (Datta, A.; Kin-Choong Yow) |
| Abstract | Research done in two aspects of robot localization and mapping are presented. An online fast learning FLANN, capable of learning location specific spatio-temporally stable visual features is developed. A technique for building oriented place maps using vestibular sensory information that can store multiple pose information of objects is investigated. Unlike most localization and mapping techniques ours does not require any depth estimation and can also handle dynamically changing environments. The system is tested in indoor environments, ranging from very simple to extremely cluttered ones. Preliminary research results show good generalization and learning capabilities of the network and improved localization using multiple oriented place maps. |
| Starting Page | 2507 |
| Ending Page | 2514 |
| File Size | 10021352 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781457706523 |
| ISSN | 1062922X |
| e-ISBN | 9781457706530 |
| DOI | 10.1109/ICSMC.2011.6084054 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-10-09 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Neurons Computer architecture Visualization Microprocessors Cameras Simultaneous localization and mapping neural network robot localization and mapping place cell place map online learning |
| Content Type | Text |
| Resource Type | Article |
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