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

Kyohei Otsu, Masatsugu Otsuki, Genya Ishigami, Takashi Kubota

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationAn Edition of the Presented Papers from the 1st International Conference on Robot Intelligence Technology and Applications
PublisherSpringer Verlag
Pages405-414
Number of pages10
ISBN (Print)9783642373732
DOIs
Publication statusPublished - 2013 Jan 1
Externally publishedYes
Event1st International Conference on Robot Intelligence Technology and Applications, RiTA 2012 - Gwangju, Korea, Republic of
Duration: 2012 Dec 162012 Dec 18

Publication series

NameAdvances in Intelligent Systems and Computing
Volume208 AISC
ISSN (Print)2194-5357

Other

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

    Fingerprint

Keywords

  • Feature detection
  • Outdoor environment
  • Visual odometry

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Otsu, K., Otsuki, M., Ishigami, G., & Kubota, T. (2013). An examination of feature detection for real-time visual odometry in untextured natural terrain. In An Edition of the Presented Papers from the 1st International Conference on Robot Intelligence Technology and Applications (pp. 405-414). (Advances in Intelligent Systems and Computing; Vol. 208 AISC). Springer Verlag. https://doi.org/10.1007/978-3-642-37374-9_39