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Intelligent Service Robotics

, Volume 8, Issue 2, pp 105–114 | Cite as

RGB-D SLAM using vanishing point and door plate information in corridor environment

  • Yonghoon Ji
  • Atsushi Yamashita
  • Hajime Asama
Original Research Paper

Abstract

This paper proposes a novel approach to an RGB-D simultaneous localization and mapping (SLAM) system that uses the vanishing point and door plates in a corridor environment simultaneously for navigation. To increase the stability of the SLAM process in such an environment, the vanishing point and door plates are utilized as landmarks for extended Kalman filter-based SLAM (i.e., EKF SLAM). The vanishing point is a semi-global unique feature usually observed in the corridor frontage, and a door plate has strong signature information (i.e., the room number) for the data association process. Thus, using these types of reliable features as landmarks maintains the stability of the SLAM process. A dense 3D map is represented by an octree structure that includes room number information, which can be useful semantic information. The experimental results showed that the proposed scheme yields a better performance than previous SLAM systems.

Keywords

SLAM RGB-D sensor Vanishing point Door plate Mobile robot 

References

  1. 1.
    Thrun S, Burgard W, Fox D (2005) Probabilistic robotics. The MIT Press, New YorkzbMATHGoogle Scholar
  2. 2.
    Lemaire T, Lacroix S, Sola J (2005) A Practical 3D bearing-only SLAM Algorithm. In: Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 2449–2454Google Scholar
  3. 3.
    Smith P, Reid I, Davison A (2006) Real-time monocular SLAM with straight lines. In: Proceedings of the 17th British machine vision conference, pp 17–26Google Scholar
  4. 4.
    Bosse M, Rikoski R, Leonard J, Teller S (2003) Vanishing points and three-dimensional lines from omnidirectional video. Vis Comput 19(6):417–430CrossRefGoogle Scholar
  5. 5.
    Kawanishi R, Yamashita A, Kaneko T, Asama H (2013) Parallel line-based structure from motion by using omnidirectional camera in textureless scene. Adv Robot 27(1):19–32CrossRefGoogle Scholar
  6. 6.
    Lee YH, Nam C, Lee KY, Li YS, Yeon SY, Doh NL (2009) VPass: algorithmic compass using vanishing points in indoor environments. In: Proceedings of the 2009 IEEE/RSJ international conference on intelligent robots and systems, pp 936–941Google Scholar
  7. 7.
    Zhang G, Suh IH (2012) A vertical and floor line-based monocular SLAM system for corridor environments. Int J Control Autom Syst 10(3):547–557CrossRefGoogle Scholar
  8. 8.
    Norling ER (2008) Perspective made easy. BN Publishing, New YorkGoogle Scholar
  9. 9.
    Shufelt JA (1999) Performance evaluation and analysis of vanishing point detection techniques. IEEE Trans Pattern Anal Mach 21(3):282–288CrossRefGoogle Scholar
  10. 10.
    Baggio DL, Emami S, Escriva DM, Ievgen K, Mahmood N (2012) Mastering openCV with practical computer vision projects. Packt Publishing, New YorkGoogle Scholar
  11. 11.
    Triebel R, Pfaff P, Burgard W (2006) Multi-level surface maps for outdoor terrain mapping and loop closing. In: Proceedings of the 2006 IEEE/RSJ international conference on intelligent robots and systems pp 2276–2282Google Scholar
  12. 12.
    Kim S, Kang J, Chung MJ (2013) Probabilistic voxel mapping using an adaptive confidence measure of stereo matching. Intell Serv Robot 6(2):89–99Google Scholar
  13. 13.
    Horunge A, Wurm KM, Bennewitz M, Stachniss C, Burgard W (2013) OctoMap: an efficient probabilistic 3D mapping framework based on Octrees. Autonom Robots 34(3):189–206CrossRefGoogle Scholar
  14. 14.

Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Graduate School of EngineeringThe University of TokyoTokyoJapan

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