Adelaide Research & Scholarship
Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/139965
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| Type: | Journal article |
| Title: | Visual Place Recognition: A Tutorial |
| Author: | Schubert, S. Neubert, P. Garg, S. Milford, M. Fischer, T. |
| Citation: | IEEE Robotics and Automation magazine, 2023; 2-16 |
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
| Issue Date: | 2023 |
| ISSN: | 1070-9932 1558-223X |
| Statement of Responsibility: | Stefan Schubert, Peer Neubert, Sourav Garg, Michael Milford, and Tobias Fischer |
| Abstract: | Localization is an essential capability for mobile robots, enabling them to build a comprehensive representation of their environment and interact with the environment effectively toward a goal. A rapidly growing field of research in this area is visual place recognition (VPR), which is the ability to recognize previously seen places in the world based solely on images. |
| Keywords: | Simultaneous localization and mapping; Tutorials; Visualization; Pipelines; Global navigation satellite system; Robots; History |
| Description: | OnlinePubl |
| Rights: | © 2023 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. 2 For more information, see https://creativecommons.org/licenses/by/4.0/ |
| DOI: | 10.1109/mra.2023.3310859 |
| Grant ID: | http://purl.org/au-research/grants/arc/FL210100156 |
| Published version: | http://dx.doi.org/10.1109/mra.2023.3310859 |
| Appears in Collections: | Australian Institute for Machine Learning publications |
Files in This Item:
| File | Description | Size | Format | |
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| hdl_139965.pdf | 1.93 MB | Adobe PDF | View/Open |
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