Vision Controlled Grasping by Means of an Intelligent Robot Hand

  • Giulio Milighetti
  • Moritz Ritter
  • Helge-Björn Kuntze


In this paper a new visual servoing concept for dynamic grasping for humanoid robots will be presented. It relies on a stereo camera in the robot head for wide range observing in combination with a miniaturized close range camera integrated in a five finger hand. By optimal fusion of both camera information using a fuzzy decision making algorithm a robust visually controlled grasping of objects is achieved even in the case of disturbed signals or dynamic obstacles.


Humanoid Robot Intelligent Robot Stereo Camera Visual Servoing Dynamic Obstacle 
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  1. 1.
    Milighetti, G., Kuntze, H.-B.: Multi-sensor controlled skills for humanoid robots. In: Proceedings of the 8th International IFAC Symposium on Robot Control (SYROCO) (September 2006)Google Scholar
  2. 2.
    Hill, J., Park, W.T.: Real time control of a robot with a mobile camera. In: Proceedings of the 9th International Symposium on Industrial Robots, Washington, DC (March 1979)Google Scholar
  3. 3.
    Martinet, P., Chaumette, F., Hashimoto, K., Malis, E.: Tutorial on advanced visual servoing. In: International Conference on Robotic Systems, Tutorial (September 2004),
  4. 4.
    Asfour, T., Regenstein, K., Azad, P., Schröeder, J., Bierbaum, A., Vahrenkamp, N., Dillmann, R.: Armar-iii: An integrated humanoid platform for sensory-motor control. In: Proceedings of the IEEE International Conference on Humanoid Robots, Genoa, Italy (December 2006)Google Scholar
  5. 5.
    Kuntze, H.-B.: Closed-loop algorithms for industrial robots - a state of the art. Process Automation 1, 35–46 (1984)Google Scholar
  6. 6.
    Lippiello, V., Siciliano, B., Villani, L.: Position-based visual servoing in industrial multirobot cells using a hybrid camera configuration. IEEE Transactions on Robotics and Automation 23(1), 73–86 (2007)Google Scholar
  7. 7.
    Agapakis, J.E., Katz, J.M., Friedman, J.M., Epstein, G.N.: Vision-aided robotic welding: An approach and a flexible implementation. International Journal of Robotic Research 9(5), 17–34 (1990)CrossRefGoogle Scholar
  8. 8.
    Namba, K., Maru, N.: Positioning control of the arm of the humanoid robot by linear visual servoing. In: Proceedings of the IEEE International Conference on Robotics and Automation, Taipei, Taiwan (September 2003)Google Scholar
  9. 9.
    Morikawa, S., Senoo, T., Namiki, A., Ishikawa, M.: Realtime collision avoidance using a robot manipulator with light-weight small high-speed vision systems. In: Proceedings of the IEEE International Conference on Robotics and Automation, Rome, Italy (April 2007)Google Scholar
  10. 10.
    Schulz, S., Pylatiuk, C., Kargov, A., Oberle, R., Bretthauer, G.: Progress in the development of anthropomorphic fluidic hands for a humanoid robot. In: Proceedings of the 4th International Conference on Humanoid Robots vol. 2 (November 2004)Google Scholar
  11. 11.
    Milighetti, G., Kuntze, H.-B.: On the discrete-continuous control of basic skills for humanoid robots. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (October 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Giulio Milighetti
    • 1
  • Moritz Ritter
    • 1
  • Helge-Björn Kuntze
    • 1
  1. 1.Fraunhofer-Institute for Information and Data Processing (IITB)KarlsruheGermany

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