• DocumentCode
    137649
  • Title

    Vision guided robotic block stacking

  • Author

    Macias, Nathanael ; Wen, J.

  • Author_Institution
    Appl. Phys. Lab., Laurel, MD, USA
  • fYear
    2014
  • fDate
    14-18 Sept. 2014
  • Firstpage
    779
  • Lastpage
    784
  • Abstract
    Industrial robots are precise and efficient at performing repetitive tasks. However, robots lack the ability to recognize and manipulate objects. They rely on human operators to translate the desired task into a set of operations that it can perform. The research area of bin-picking aims to provide robots with the ability to manipulate randomly ordered objects in unstructured environments. This research focuses on developing a robust vision guided robotic block pick-up and stacking system. We use binary markers to aid in block identification and localization, a custom 3D-printed gripper for robust grasping, and planning algorithms to determine the grasp sequence. By integrating a low-cost webcam with an industrial robot, our system is able to observe the block locations in a random pile, determine the appropriate response necessary to grasp, and sequence to remove blocks from a pile.
  • Keywords
    bin packing; grippers; industrial manipulators; object recognition; path planning; robot vision; bin-picking; binary markers; block identification; block localization; custom 3D-printed gripper; grasp sequence determination; industrial robots; low-cost webcam; object recognition; planning algorithms; random pile; randomly ordered object manipulation; robust grasping; robust vision guided robotic block pick-up and stacking system; unstructured environments; Cameras; Grippers; Robot vision systems; Service robots;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on
  • Conference_Location
    Chicago, IL
  • Type

    conf

  • DOI
    10.1109/IROS.2014.6942647
  • Filename
    6942647