Towards the Robotic Co-Worker

  • Sami Haddadin
  • Michael Suppa
  • Stefan Fuchs
  • Tim Bodenmüller
  • Alin Albu-Schäffer
  • Gerd Hirzinger
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 70)


Recently, robots have gained capabilities in both sensing and actuation, which enable operation in the proximity of humans. Even direct physical interaction has become possible without suffering the decrease in speed and payload. The DLR Lightweight Robot III (LWR-III), whose technology is currently being transferred to the robot manufacturer KUKA Roboter GmbH, is such a device capable of realizing various features crucial for direct interaction with humans. Impedance control and collision detection with adequate reaction are key components for enabling “soft and safe” robotics. The implementation of a sensor based robotic co-worker that brings robots closer to humans in industrial settings and achieve close cooperation is an important goal in robotics. Despite being a common vision in robotics it has not become reality yet, as there are various open questions still to be answered. In this paper a sound concept and a prototype implementation of a co-worker scenario are developed in order to demonstrate that stateof- the-art technology is now mature enough to reach this aspiring aim. We support our ideas by addressing the industrially relevant bin-picking problem with the LWR-III, which is equipped with a Time-of-Flight camera for object recognition and the DLR 3D-Modeller for generating accurate environment models. The paper describes the sophisticated control schemes of the robot in combination with robust computer vision algorithms, which lead to a reliable solution for the addressed problem. Strategies are devised for safe interaction with the human during task execution, state depending robot behavior, and the appropriate mechanisms, to realize robustness in partially unstructured environments.


Collision Avoidance Collision Detection Task Execution Iterative Close Point Impedance Control 
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.


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  1. 1.
    Moshner, R.: From handiman to hardiman. Trans. Soc. Autom. Eng. 16, 588–597 (1967)Google Scholar
  2. 2.
    Yamada, Y., Konosu, H., Morizono, T., Umetani, Y.: Proposal of Skill-Assist: a system of assisting human workers by reflecting their skills in positioning tasks. In: IEEE International Conference on Systems, Man, and Cybernetics (SMC 1999), Tokyo, Japan, pp. 11–16 (1999)Google Scholar
  3. 3.
    Hirzinger, G., Heindl, J.: Sensor programming - a new way for teaching a robot paths and forces. In: International Conference on Robot Vision and Sensory Controls (RoViSeC3), Cambridge, Massachusetts, USA (1993)Google Scholar
  4. 4.
    Stemmer, A., Albu-Schäffer, A., Hirzinger, G.: An Analytical Method for the Planning of Robust Assembly Tasks of Complex Shaped Planar Parts. In: Int. Conf. on Robotics and Automation (ICRA 2007), Rome, Italy, pp. 317–323 (2007)Google Scholar
  5. 5.
    Yamada, Y., Hirasawa, Y., Huand, S., Umetani, Y.: Fail-Safe Human/Robot Contact in the Safety Space. In: IEEE Int. Workshop on Robot and Human Communication, pp. 59–64 (1996)Google Scholar
  6. 6.
    Zinn, M., Khatib, O., Roth, B.: A New Actuation Approach for Human Friendly Robot Design. Int. J. of Robotics Research 23, 379–398 (2004)CrossRefGoogle Scholar
  7. 7.
    Bicchi, A., Tonietti, G.: Fast and Soft Arm Tactics: Dealing with the Safety-Performance Trade-Off in Robot Arms Design and Control. IEEE Robotics & Automation Mag. 11, 22–33 (2004)CrossRefGoogle Scholar
  8. 8.
    Haddadin, S., Albu-Schäffer, A., Hirzinger, G.: Safe Physical Human-Robot Interaction: Measurements, Analysis & New Insights. In: International Symposium on Robotics Research (ISRR 2007), Hiroshima, Japan, pp. 439–450 (2007)Google Scholar
  9. 9.
    Haddadin, S., Albu-Schäffer, A., Hirzinger, G.: Safety Evaluation of Physical Human-Robot Interaction via Crash-Testing. In: Robotics: Science and Systems Conference (RSS 2007), Atlanta, USA, pp. 217–224 (2007)Google Scholar
  10. 10.
    Haddadin, S., Albu-Schäffer, A., De Luca, A., Hirzinger, G.: Collision Detection & Reaction: A Contribution to Safe Physical Human-Robot Interaction. In: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2008), Nice, France, pp. 3356–3363 (2008)Google Scholar
  11. 11.
    Kulic, D., Croft, E.A.: Affective State Estimation for Human-Robot Interaction. IEEE Transactions on Robotics 23(5), 991–1000 (2007)CrossRefGoogle Scholar
  12. 12.
    Edsinger, A., Kemp, C.C.: Human-Robot Interaction for Cooperative Manipulation: Handing Objects to One Another. In: IEEE International Symposium on Robot & Human Interactive Communication (RO-MAN 2007), Jeju Island, Korea, pp. 1167–1172 (2007)Google Scholar
  13. 13.
    Dominey, P.F., Metta, G., Natale, L., Nori, F.: Anticipation and Initiative in Dialog and Behavior During Cooperative Human-Humanoid Interaction. In: IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS 2008), Daejeon, Korea, pp. 693–699 (2008)Google Scholar
  14. 14.
    Haddadin, S.: Towards the Human-Friendly Robotic Co-Worker. Master’s thesis, Technical University of Munich (TUM) & German Aerospace Center (DLR) (May 2009)Google Scholar
  15. 15.
    Brock, O., Khatib, O.: Elastic Strips: A Framework for Motion Generation in Human Environments. Int. J. Robotics Research 21(12), 1031–1052 (2002)CrossRefGoogle Scholar
  16. 16.
    Albu-Schäffer, A., Ott, C., Hirzinger, G.: A Unified Passivity-based Control Framework for Position, Torque and Impedance Control of Flexible Joint Robots. Int. J. of Robotics Research 26, 23–39 (2007)CrossRefGoogle Scholar
  17. 17.
    Siciliano, B., Khatib, O. (eds.): Springer Handbook of Robotics. Springer, Heidelberg (2008)MATHGoogle Scholar
  18. 18.
    Suppa, M., Kielhoefer, S., Langwald, J., Hacker, F., Strobl, K.H., Hirzinger, G.: The 3D-Modeller: A Multi-Purpose Vision Platform. In: Int. Conf. on Robotics and Automation (ICRA), Rome, Italy, pp. 781–787 (2007)Google Scholar
  19. 19.
    Hacker, F., Dietrich, J., Hirzinger, G.: A Laser-Triangulation Based Miniaturized 2-D Range-Scanner as Integral Part of a Multisensory Robot-Gripper. In: EOS Topical Meeting on Optoelectronic Distance/Displacement Measurements and Applications, Nantes, France (1997)Google Scholar
  20. 20.
    Strobl, K.H., Wahl, E., Sepp, W., Bodenmueller, T., Seara, J., Suppa, M., Hirzinger, G.: The DLR Hand-guided Device: The Laser-Stripe Profiler. In: Int. Conf. on Robotics and Automation (ICRA 2004), New Orleans, USA, pp. 1927–1932 (2004)Google Scholar
  21. 21.
    Suppa, M.: Autonomous robot work cell exploration using multisensory eye-in-hand systems. Ph.D. dissertation, Gottfried Wilhelm Leibniz Universität Hannover (2007)Google Scholar
  22. 22.
    Fuchs, S., Hirzinger, G.: Extrinsic and Depth Calibration of ToF-Cameras. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2008), Anchorage, USA, pp. 1–6 (2008)Google Scholar
  23. 23.
    Sepp, W., Fuchs, S., Hirzinger, G.: Hierarchical Featureless Tracking for Position-Based 6-DoF Visual Servoing. In: IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2006), Beijing, China, pp. 4310–4315 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sami Haddadin
    • 1
  • Michael Suppa
    • 1
  • Stefan Fuchs
    • 1
  • Tim Bodenmüller
    • 1
  • Alin Albu-Schäffer
    • 1
  • Gerd Hirzinger
    • 1
  1. 1.Institute of Robotics and MechatronicsDLR e.V. - German Aerospace CenterWesslingGermany

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