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Kuroda Yoji
Department Undergraduate School , School of Science and Technology Position Professor |
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| Language | Japanese |
| Publication Date | 2015/04 |
| Type | Academic Journal |
| Peer Review | Peer reviewed |
| Title | Robust Localization in Environmental Variation Using GPS and Sequential Images to Sensor Integration |
| Contribution Type | Co-authored (other than first author) |
| Journal | Transactions of the Society of Instrument and Control Engineers |
| Journal Type | Japan |
| Publisher | the Society of Instrument and Control Engineers |
| Volume, Issue, Page | pp.57-63 |
| Author and coauthor | K. Kiuchi, T. YOKOTA, T. Saito, and Y. Kuroda |
| Details | In this paper, we propose a mobile robot localization system in frequent GPS-denied situations. We utilize multiple observations that are obtained from sequential appearance-based place recognition and GPS. Using GPS observations has still some challenging problems such as multipath or signal lost under environments where there are tall buildings nearby. The appearance-based place recognition that is combined with positional information has capability to overcome the issue. We apply both of observations derived from GPS and appearance-based place recognition to a mobile robot localization for the sake of achieving robust localization. Moreover sequential appearance-based place recognition makes it possible to recognize their own position even when we navigate a robot at night. Our system uses not only multiple observations but also dead reckoning with gyrodometry model. Our experiments are performed over aggregate 5300m trajectory approximately that contain a 1600m outdoor route in different seasons and at different times, and a 500 m short-range route to verify its validity. |
| URL for researchmap | http://adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2015TSICE..51...57K&link_type=EJOURNAL |