An examination of feature detection for real-time visual odometry in untextured natural terrain

Kyohei Otsu, Masatsugu Otsuki, Genya Ishigami, Takashi Kubota

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Estimating the position of a robot is an essential requirement for autonomous mobile robots. Visual Odometry is a promising localization method in slippery natural terrain, which drastically degrades the accuracy of Wheel Odometry, while relying neither on other infrastructure nor any prior knowledge. Visual Odometry, however, suffers from the instability of feature extraction from the untextured natural terrain. To date, a number of feature detectors have been proposed for stable feature detection. This paper compares commonly used detectors in terms of robustness, localization accuracy and computational efficiency, and points out their trade-off problems among those criteria. To solve the problem, a hybrid algorithm is proposed which dynamically switches between multiple detectors according to the texture of terrain. Validity of the algorithm is proved by the simulation using dataset at volcanic areas in Japan.

本文言語English
ホスト出版物のタイトルAn Edition of the Presented Papers from the 1st International Conference on Robot Intelligence Technology and Applications
出版社Springer Verlag
ページ405-414
ページ数10
ISBN(印刷版)9783642373732
DOI
出版ステータスPublished - 2013 1 1
外部発表はい
イベント1st International Conference on Robot Intelligence Technology and Applications, RiTA 2012 - Gwangju, Korea, Republic of
継続期間: 2012 12 162012 12 18

出版物シリーズ

名前Advances in Intelligent Systems and Computing
208 AISC
ISSN(印刷版)2194-5357

Other

Other1st International Conference on Robot Intelligence Technology and Applications, RiTA 2012
CountryKorea, Republic of
CityGwangju
Period12/12/1612/12/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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