• DocumentCode
    569544
  • Title

    A method for mobile robot obstacle avoidance based on stereo vision

  • Author

    Chen, Meng ; Cai, Zhihao ; Wang, Yingxun

  • Author_Institution
    Sch. of Autom. Sci. & Electr. Eng., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
  • fYear
    2012
  • fDate
    25-27 July 2012
  • Firstpage
    94
  • Lastpage
    98
  • Abstract
    An obstacle avoidance method is researched based on stereo vision by using Pioneer3-AT wheeled mobile robots as research platform. Locating obstacles is realized quickly by means of image segmentation and stereo vision algorithm which can separate obstacles from the background and stereo match their contour features with the stereo vision calibration results to get the spatial point for 3D reconstruction. The obstacle avoidance method uses stereo vision and sonar sensors working cooperatively to get the information of the obstacles in the vicinity of the robot. Fuzzy logic control algorithm is adopted to avoid collision and bypass the enroute obstacles. In the development environment of Visual C++ and OpenCV, the validity and effectiveness of the method has been demonstrated in achieving the task of evading obstacles. The method is simple and quick which is significant for the further navigation.
  • Keywords
    C++ language; Visual BASIC; collision avoidance; image segmentation; mobile robots; sonar imaging; stereo image processing; 3D reconstruction; OpenCV; Pioneer3-AT wheeled mobile robots; Visual C++; contour features; fuzzy logic control algorithm; image segmentation; mobile robot obstacle avoidance; obstacle avoidance method; sonar sensors; stereo vision algorithm; stereo vision calibration; Calibration; Cameras; Collision avoidance; Mobile robots; Robot vision systems; Sonar; Stereo vision; 3D Reconstruction; Image Segmentation; Obstacle Avoidance; Stereo Matching;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Informatics (INDIN), 2012 10th IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-0312-5
  • Type

    conf

  • DOI
    10.1109/INDIN.2012.6300848
  • Filename
    6300848