• DocumentCode
    2545682
  • Title

    Optical flow odometry with robustness to self-shadowing

  • Author

    Seegmiller, Neal ; Wettergreen, David

  • Author_Institution
    Carnegie Mellon University, Robotics Institute, USA
  • fYear
    2011
  • fDate
    25-30 Sept. 2011
  • Firstpage
    613
  • Lastpage
    618
  • Abstract
    An optical flow odometry method for mobile robots using a single downward-looking camera is presented. The method is robust to the robot´s own moving shadow and other sources of error. Robustness derives from two techniques: prevention of feature selection on or near shadow edges and elimination of outliers based on inconsistent motion. In tests where the robot´s shadow dominated the image, prevention of feature selection near shadow edges allowed accurate velocity estimation when outlier rejection alone failed. Performance was evaluated on two robot platforms and on multiple terrain types at speeds up to 2 m/s.
  • Keywords
    Adaptive optics; Cameras; Feature extraction; Image edge detection; Robot vision systems; Robustness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    2153-0858
  • Print_ISBN
    978-1-61284-454-1
  • Type

    conf

  • DOI
    10.1109/IROS.2011.6094670
  • Filename
    6094670