• DocumentCode
    2772822
  • Title

    Trajectory tracking control of the guiding and following mobile robots: Elliptic collision-Free approach

  • Author

    Yu, Wen-Shyong ; Lin, Chih-Hao

  • Author_Institution
    Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    In this paper, a trajectory tracking control strategy by elliptic collision-Free approach is proposed for guiding and following mobile robots. Each robot is setup with a single eye camera to capture the image of a guiding robot or obstacle. The image between them is converted to a gray form, and then to the gradient for each pixel of Gaussian pyramid level to estimate the motion parameters, disturbances, or obstacles. Successive images for a moving object are used to estimate or recognize the foreground, guiding robot, and obstacles by calculating the gravity of the moving object, and then the following mobile robot will follow the trajectory of the guiding one. On the contrary, the following mobile robot turns out to serve as a guiding one when there is no gravity. Furthermore, the elliptic collision-free path will be used for obstacle gravity and keep going until the final destination is achieved. Finally, experimental results will be used to show the effectiveness of the proposed method.
  • Keywords
    Gaussian processes; cameras; collision avoidance; image recognition; mobile robots; motion estimation; object tracking; parameter estimation; robot vision; trajectory control; Gaussian pyramid level; disturbance estimation; elliptic collision-free path; eye camera; following mobile robots; foreground recognition; gradient image; gray image; guiding mobile robots; guiding robot image; guiding robot recognition; motion parameter estimation; obstacle estimation; obstacle gravity; obstacle image; obstacle recognition; trajectory tracking control; Collision avoidance; Gravity; Mobile robots; Robot kinematics; Trajectory; Wheels; elliptic collision-free approach; guiding and following mobile robots; obstacles; trajectory tracking control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2012 International Joint Conference on
  • Conference_Location
    Brisbane, QLD
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4673-1488-6
  • Electronic_ISBN
    2161-4393
  • Type

    conf

  • DOI
    10.1109/IJCNN.2012.6252564
  • Filename
    6252564