• DocumentCode
    2033677
  • Title

    Self-learning vision-guided robots for searching and grasping objects

  • Author

    Nguyen, Minh-Chid ; Graefe, Volker

  • Author_Institution
    Inst. of Meas. Sci., Bundeswehr Univ., Munich, Germany
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    1633
  • Abstract
    An approach to control vision-guided robots is introduced. It allows searching and grasping differently shaped objects that may be located anywhere in the robot´s work space, even not visible in the initial fields of view of cameras. It eliminates the need for a calibration of the robot and of the vision system, it uses no world coordinates and no inverse perspective or kinematic transformations, and it comprises an automatic adaptation to changing parameters. The approach has been implemented on a calibration-free vision-guided manipulator with five degrees of freedom (DOF) and was evaluated in real-word experiments
  • Keywords
    feature extraction; learning (artificial intelligence); manipulators; position control; robot vision; stereo image processing; automatic adaptation; calibration-free vision-guided manipulator; five degrees of freedom manipulator; grasping; searching; self-learning vision-guided robots; Calibration; Cameras; Grippers; Jacobian matrices; Orbital robotics; Robot control; Robot kinematics; Robot sensing systems; Robot vision systems; Robotics and automation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1050-4729
  • Print_ISBN
    0-7803-5886-4
  • Type

    conf

  • DOI
    10.1109/ROBOT.2000.844830
  • Filename
    844830