• DocumentCode
    1382421
  • Title

    Moving obstacle detection from a navigating robot

  • Author

    Nair, Dinesh ; Aggarwal, Jagdishkumar K.

  • Author_Institution
    Nat. Instrum. Corp., Austin, TX, USA
  • Volume
    14
  • Issue
    3
  • fYear
    1998
  • fDate
    6/1/1998 12:00:00 AM
  • Firstpage
    404
  • Lastpage
    416
  • Abstract
    This paper presents a system that detects unexpected moving obstacles that appear in the path of a navigating robot, and estimates the relative motion of the object with respect to the robot. The system is designed for a robot navigating in a structured environment with a single wide-angle camera. The system uses polar mapping to simplify the segmentation of the moving object from the background. The polar mapping is performed with the focus of expansion as the center. A vision-based algorithm that uses the vanishing points of segments extracted from a scene in a few 3D orientations provides an accurate estimate of the robot orientation. In the transformed space qualitative estimate of moving obstacles is obtained by detecting the vertical motion of edges extracted in a few specified directions. Relative motion information about the obstacle is then obtained by computing the time to impact between the obstacles and robot from the radial component of the optical flow. The system was implemented and on an indoor mobile robot
  • Keywords
    edge detection; feature extraction; image sequences; mobile robots; motion estimation; navigation; object recognition; path planning; robot vision; edge detection; feature extraction; focus of expansion; mobile robot; motion estimation; moving obstacle detection; navigation; optical flow; polar mapping; robot vision; vanishing points; Cameras; Data mining; Layout; Motion detection; Motion estimation; Navigation; Object detection; Optical computing; Orbital robotics; Robot vision systems;
  • fLanguage
    English
  • Journal_Title
    Robotics and Automation, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1042-296X
  • Type

    jour

  • DOI
    10.1109/70.678450
  • Filename
    678450