Kuroda Yoji
   Department   Undergraduate School  , School of Science and Technology
   Position   Professor
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 TypeJapan
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