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Visual Odometry

Visual Odometry
  • Research Background
    • In the case of environments in which a GPS signal cannot be acquired (i.e forests, buildings, and concentrated urban areas), an alternative localization method is needed. 
    • Instead of using costly sensors like GPS or laser scanners, a camera is an inexpensive sensor with potential for various applications.

    


  • Research Objectives
    • Using a stereo-camera, relative motion between each frame is estimated and robot trajectory is drawn.
    • Feature extraction, feature matching, outlier removal and motion estimation is the structure of this algorithm.
    • Furthermore, mono-camera and Kinect are to be utilized to reduce processing time and to deal with dark environments. 
    • Optimal algorithm that is robust in outdoor environments (where light levels and shadows must be accounted for) is also being researched.
    • In the future, drift-error will be resolved using landmarks. 

  • Research Output
    • Improved accuracy was shown using visual odometry (red, stereo-camera) compared to odometry (blue, IMU+encoder)