• DocumentCode
    3284354
  • Title

    An intelligent vision system for object localization and obstacle avoidance for an indoor service robot

  • Author

    Hema, C.R. ; Paulraj, M.P. ; Adom, Abdul Hamid Bin ; Sim, K.F. ; Palaniappan, Rajkumar

  • Author_Institution
    Fac. of Eng., Karpagam Univ., Coimbatore, India
  • fYear
    2011
  • fDate
    19-20 Dec. 2011
  • Firstpage
    117
  • Lastpage
    122
  • Abstract
    Housekeeping robots are service robots specially designed to perform housekeeping tasks such as cleaning and vacuuming. In this research an intelligent vision system for object localization and obstacle avoidance for an indoor service robot was developed. The vision system aids in identifying objects and obstacles in a controlled environment. The system comprises of a digital camera which is placed on the front panel of the robot. Captured images are processed to segment object of the image. A simple neural network model was developed to identify obstacles and objects. Visual servoing is used to locate the object that fall out of the gripper range and visual range as well. The developed vision system has successfully tested on the house keeping robot for real time navigation and pick & place operation.
  • Keywords
    collision avoidance; grippers; image segmentation; neural nets; object detection; robot vision; service robots; video cameras; visual servoing; digital camera; gripper; housekeeping robots; image segmentation; indoor service robot; intelligent vision system; neural network model; object identification; object localization; obstacle avoidance; pick & place operation; real time navigation; visual servoing; Cameras; Computer crashes; Educational institutions; Image segmentation; Robot vision systems; Visualization; Object & obstacle identification; neural network; real time navigation; visual servoing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Research and Development (SCOReD), 2011 IEEE Student Conference on
  • Conference_Location
    Cyberjaya
  • Print_ISBN
    978-1-4673-0099-5
  • Type

    conf

  • DOI
    10.1109/SCOReD.2011.6148719
  • Filename
    6148719