• DocumentCode
    1294208
  • Title

    Selective stabilization of images acquired by unmanned ground vehicles

  • Author

    Yao, Y.S. ; Chellapa, R.

  • Author_Institution
    Pacific Bell, San Ramon, CA, USA
  • Volume
    13
  • Issue
    5
  • fYear
    1997
  • fDate
    10/1/1997 12:00:00 AM
  • Firstpage
    693
  • Lastpage
    708
  • Abstract
    This paper studies the problem of selective stabilization of images acquired by a camera mounted on a vehicle navigating a rough terrain. Selective stabilization is defined here as the separation of rotational components into smooth and residual oscillatory rotations. We consider both kinematic and kinetic models suitable for capturing these phenomena and achieve their separation. A scheme for detecting the occurrence and disappearance of smooth rotation is devised, and appropriate dynamic laws are employed to achieve selective stabilization. As a by product of the selective stabilization algorithm, 3-D locations of close feature points are estimated in a stabilized frame of reference, thus providing more useful structural information. Experiments using synthetic images for different scenarios show encouraging results of the proposed approach
  • Keywords
    Kalman filters; image sequences; mobile robots; motion estimation; nonlinear filters; path planning; recursive estimation; robot dynamics; robot kinematics; robot vision; vehicles; 3D locations; dynamic laws; kinematic models; kinetic models; residual oscillatory rotations; rotational components; rough terrain; selective stabilization; smooth rotations; structural information; synthetic images; unmanned ground vehicles; Cameras; Feedback control; Image generation; Kinematics; Kinetic theory; Land vehicles; Motion detection; Navigation; Road vehicles; Vehicle dynamics;
  • fLanguage
    English
  • Journal_Title
    Robotics and Automation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1042-296X
  • Type

    jour

  • DOI
    10.1109/70.631231
  • Filename
    631231