• DocumentCode
    716907
  • Title

    Omnidirectional-vision-based estimation for containment detection of a robotic mower

  • Author

    Junho Yang ; Soon-Jo Chung ; Hutchinson, Seth ; Johnson, David ; Kise, Michio

  • Author_Institution
    Dept. of Mech. Sci. & Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2015
  • fDate
    26-30 May 2015
  • Firstpage
    6344
  • Lastpage
    6351
  • Abstract
    In this paper, we present an omnidirectional-vision-based localization and mapping system which can detect whether a robotic mower is contained in a permitted area. We exploit a robot-centric mapping framework that exploits a differential equation of motion of the landmarks, which are referenced with respect to the robot body frame. The estimator in our system generates a 3D point-based map with landmarks. Concurrently, the estimator defines a boundary of the mowing area with the estimated trajectory of the mower. The estimated boundary and the landmark map are provided for the estimation of the mowing location and for the containment detection. We validate the effectiveness of our system through numerical simulations and present the results of the outdoor experiment that we conducted with our robotic mower.
  • Keywords
    SLAM (robots); differential equations; mobile robots; robot vision; 3D point-based map; containment detection; landmark motion differential equation; omnidirectional-vision-based estimation; omnidirectional-vision-based localization-and-mapping system; outdoor experiment; permitted area; robot body frame; robot-centric mapping framework; robotic mower; Cameras; Estimation; Robot kinematics; Robot vision systems; Simultaneous localization and mapping;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation (ICRA), 2015 IEEE International Conference on
  • Conference_Location
    Seattle, WA
  • Type

    conf

  • DOI
    10.1109/ICRA.2015.7140090
  • Filename
    7140090