• DocumentCode
    181709
  • Title

    LAPS-II: 6-DoF day and night visual localisation with prior 3D structure for autonomous road vehicles

  • Author

    Maddern, Will ; Stewart, Alexander D. ; Newman, Paul

  • Author_Institution
    Dept. Eng. Sci., Univ. of Oxford, Oxford, UK
  • fYear
    2014
  • fDate
    8-11 June 2014
  • Firstpage
    330
  • Lastpage
    337
  • Abstract
    Robust and reliable visual localisation at any time of day is an essential component towards low-cost autonomy for road vehicles. We present a method to perform online 6-DoF visual localisation across a wide range of outdoor illumination conditions throughout the day and night using a 3D scene prior collected by a survey vehicle. We propose the use of a one-dimensional illumination invariant colour space which stems from modelling the spectral properties of the camera and scene illumination in conjunction. We combine our previous work on Localisation with Appearance of Prior Structure (LAPS) with this illumination invariant colour space to demonstrate a marked improvement in our ability to localise throughout the day compared to using a conventional RGB colour space. Our ultimate goal is robust and reliable any-time localisation - an attractive proposition for low-cost autonomy for road vehicles. Accordingly, we demonstrate our technique using 32km of data collected over a full 24-hour period from a road vehicle.
  • Keywords
    cameras; image colour analysis; mobile robots; road vehicles; robot vision; 3D scene; 6-DoF day-night visual localisation; LAPS-II; RGB colour space; autonomous road vehicles; camera spectral properties; distance 32 km; localisation with appearance of prior structure; one-dimensional illumination invariant colour space; outdoor illumination conditions; prior 3D structure; scene illumination; time 24 hour; Cameras; Image color analysis; Lighting; Robustness; Sensors; Three-dimensional displays; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Vehicles Symposium Proceedings, 2014 IEEE
  • Conference_Location
    Dearborn, MI
  • Type

    conf

  • DOI
    10.1109/IVS.2014.6856471
  • Filename
    6856471