• DocumentCode
    1792225
  • Title

    Topological mapping and navigation based on visual sensor network

  • Author

    Wenbo Yuan ; Zhiqiang Cao ; Min Tan ; Jingyu Liu

  • Author_Institution
    State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China
  • fYear
    2014
  • fDate
    3-6 Aug. 2014
  • Firstpage
    1686
  • Lastpage
    1690
  • Abstract
    In this paper, a novel topological mapping approach applied to the navigation mission is proposed based on visual sensor network. Firstly, the natural objects in the scene monitored by visual sensor network are recognized through the inference model based on structural features. Then, topological nodes are designed according to the recognized objects and their spatial structure information, and topological mapping will be fulfilled. On this basis, global localization for mobile robot in camera view can be implemented with HOG feature based detection and tracking. Finally, the robot can make motion decisions for navigation. Our approach does not rely on artificial landmarks and is tested in large-scale office scene. The effectiveness of the proposed approach is verified.
  • Keywords
    image sensors; mobile robots; navigation; object detection; object recognition; object tracking; path planning; robot vision; HOG feature based detection; HOG feature based tracking; artificial landmarks; camera view; global localization; inference model; large-scale office scene; mobile robot; motion decisions; object recognition; spatial structure information; structural features; topological mapping approach; topological navigation mission; topological nodes; visual sensor network; Cameras; Feature extraction; Image segmentation; Navigation; Robot sensing systems; Visualization; Mobile robot; Navigation; Topological mapping; Visual sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
  • Conference_Location
    Tianjin
  • Print_ISBN
    978-1-4799-3978-7
  • Type

    conf

  • DOI
    10.1109/ICMA.2014.6885954
  • Filename
    6885954