Human-aware Interaction Control of Robot Manipulators Based on Force and Vision

  • Luigi Villani
  • Agostino De Santis
  • Vincenzo Lippiello
  • Bruno Siciliano
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 396)


The extension of application domains of robotics from factories to human environments leads to implementing proper strategies for close interaction between people and robots. On the one hand, small-scale industrial robots have to learn to get along with human coworkers in factories, and, on the other hand, service robots are a solution for automatizing common daily tasks in domestic environments, due to lack or high cost of human expertise.

The size of an industrial robot, or the necessary autonomous behavior of a service robot, can result in dangerous situations for humans coexisting in the robot operational domain. Therefore, physical issues must be carefully considered, since “natural” or unexpected behaviors of people during interaction with robots can result in injuries, which may be severe, when considering the current mechanical structure of robots available on the market [1].


Collision Avoidance Impedance Control Service Robot Base Frame Camera Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    De Santis, A., Siciliano, B., De Luca, A., Bicchi, A.: An atlas of physical Human Robot Interaction. Mechanism and Machine Theory 43, 253–270 (2008)zbMATHCrossRefGoogle Scholar
  2. 2.
    Zinn, M., Khatib, O., Roth, B., Salisbury, J.K.: Playing it safe. IEEE Robotics and Automation Magazine 11(2), 12–21 (2004)CrossRefGoogle Scholar
  3. 3.
    Bicchi, A., Tonietti, G.: Fast and soft-arm tactics. IEEE Robotics and Automation Magazine 11(2), 22–33 (2004)CrossRefGoogle Scholar
  4. 4.
    Hashimoto, H.: Intelligent interactive spaces – integration of IT and robotics. In: Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, pp. 85–90 (2005)Google Scholar
  5. 5.
    Hosoda, K., Igarashi, K., Asada, M.: Adaptive hybrid control for visual and force servoing in an unknown environment. IEEE Robotics and Automation Magazine 5(4), 39–43 (1998)CrossRefGoogle Scholar
  6. 6.
    Nelson, B.J., Morrow, J.D., Khosla, P.K.: Improved force control through visual servoing. In: Proceedings of American Control Conference, pp. 380–386 (1995)Google Scholar
  7. 7.
    Baeten, J., De Schutter, J.: Integrated Visual Servoing and Force Control. The Task Frame Approach. Springer, Heidelberg (2004)Google Scholar
  8. 8.
    Morel, G., Malis, E., Boudet, S.: Impedance based combination of visual and force control. In: Proceedings of IEEE International Conference on Robotics and Automation, pp. 1743–1748 (1998)Google Scholar
  9. 9.
    Olsson, T., Johansson, R., Robertsson, A.: Flexible force-vision control for surface following using multiple cameras. In: Proceedings of IEEE/RSJ International Conference on Intelligent Robots and System, pp. 798–803 (2004)Google Scholar
  10. 10.
    Siciliano, B., Villani, L.: Robot Force Control. Kluwer, Dordrecht (1999)zbMATHGoogle Scholar
  11. 11.
    Lippiello, V., Siciliano, B., Villani, L.: A position-based visual impedance control for robot manipulators. In: Proceedings of IEEE Int. Conf. on Robotics and Automation, pp. 2068–2073 (2007)Google Scholar
  12. 12.
    Lippiello, V., Siciliano, B., Villani, L.: Robot force/position control with force and visual feedback. In: Proceedings of European Control Conference, pp. 3790–3795 (2007)Google Scholar
  13. 13.
    De Santis, A., Albu-Schaeffer, A., Ott, C., Siciliano, B., Hirzinger, G.: The skeleton algorithm for self-collision avoidance of a humanoid manipulator. In: Proceedings of IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Zurich, CH (2007)Google Scholar
  14. 14.
    Hirzinger, G., Albu-Schaeffer, A., Hahnle, M., Schaefer, I., Sporer, N.: On a new generation of torque controlled light-weight robots. In: Proceedings of IEEE International Conference of Robotics and Automation, pp. 3356–3363 (2001)Google Scholar
  15. 15.
    De Santis, A., Pierro, P., Siciliano, B.: The virtual end-effectors approach for human-robot interaction. In: Lenarčič, J., Roth, B. (eds.) Advances in Robot Kinematics. Springer, Heidelberg (2006)Google Scholar
  16. 16.
    Espiau, B., Chaumette, F., Rives, P.: A new approach to visual servoing in robotics. IEEE Transactions on Robotics and Automation 8, 313–326 (1996)CrossRefGoogle Scholar
  17. 17.
    Lippiello, V., Villani, L.: Managing redundant visual measurements for accurate pose tracking. Robotica 21, 511–519 (2003)CrossRefGoogle Scholar
  18. 18.
    Villani, L., De Schutter, J.: Force control. In: Siciliano, B., Khatib, O. (eds.) Springer Handbook of Robotics. Springer, New York (2008)Google Scholar
  19. 19.
    Lippiello, V., Siciliano, B., Villani, L.: Position-based visual servoing in industrial multi-robot cells using a hybrid camera configuration. IEEE Trans. on Robotics, 73–86 (2007)Google Scholar

Copyright information

© Springer London 2009

Authors and Affiliations

  • Luigi Villani
    • 1
  • Agostino De Santis
    • 1
  • Vincenzo Lippiello
    • 1
  • Bruno Siciliano
    • 1
  1. 1.PRISMA Lab, Dipartimento di Informatica e SistemisticaUniversit‘a di Napoli Federico IINaplesItaly

Personalised recommendations