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An Image Based Algorithm to Safely Locate Human Extremities for Human-Robot Collaboration

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 7507)

Abstract

For safe human-robot collaboration a technologically diverse and redundant sensor system is developed which comprises ultrasound sensors and two monocular camera systems. The sensor system recognizes human extremities in the collaboration area in which robot and human shall work together interactively. The robot controller calculates the shortest distance between the robot and a human operator. With the fused sensor data the controller determines how to adapt the robot behavior to avoid undesired physical contact with the human operator.

Keywords

  • functional safety
  • embedded systems
  • human-robot collaboration
  • monocular machine vision
  • infrared imaging
  • safe robotics

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References

  1. ManuCyte: Modular Manufacturing Platform for Flexible, Patient-Specific Cell Cultivation. Fraunhofer Institute for Manufacturing Engineering and Automation (IPA). Nobelstr. 12, D-70569 Stuttgart, http://www.manucyte-project.eu/

  2. Heiligensetzer, P.: Aktuelle Entwicklungen bei Industrierobotern im Bereich der Mensch-Roboter Kooperation. Technical Report, Tag der Arbeitssicherheit in Fellbach (2009)

    Google Scholar 

  3. Frey, S., Fuchs, L., Kramer-Wolf, T., Kurth, M., Maibach, J., Merx, J., Schwarz, M., Stark, T., Skaletz-Karrer, S., Wimmer, M.: Dreidimensionale Sicherheit. Mensch und Automation 03, 3 (2011)

    Google Scholar 

  4. Gecks, T., Henrich, D.: SIMERO: Camera Supervised Workspace for Service Robots, Technical Report, 2nd Workshop on Advances in Service Robotics, Fraunhofer IPA (2004)

    Google Scholar 

  5. Simmons, R., Goldberg, D., Goode, A., Montemerlo, M., Roy, N., Sellner, B., Urmson, C., Bugajska, M., Coblenz, M., Macmahon, M., Perzanowski, D., Horswill, I., Zubek, R., Kortenkamp, D., Wolfe, B., Milam, T., Maxwell, B.: GRACE: An Autonomous Robot for the AAAI Robot Challenge. AI Magazine 24, 51–72 (2003)

    Google Scholar 

  6. Ebert, D.: Bildbasierte Erzeugung kollisionsfreier Transferbewegungen für Industrieroboter. Dissertation, University of Bayreuth (2003)

    Google Scholar 

  7. Garg, P., Aggarwal, N., Sofat, S.: Vision Based Hand Gesture Recognition. Engineering and Technology 49, 972–977 (2009)

    Google Scholar 

  8. Erol, A., Bebis, G., Nicolescu, M., Boyle, R., Twombly, X.: A Review on Vision-Based Full DOF Hand Motion Estimation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR (2005)

    Google Scholar 

  9. Shimada, N., Kimura, K., Shirai, Y.: Real-time 3D hand posture estimation based on 2D appearance retrieval using monocular camera. In: ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, pp. 23–30 (2001)

    Google Scholar 

  10. Kölsch, M., Turk, M.: Robust Hand Detection. In: International Conference on Automatic Face and Gesture Recognition, Seoul, Korea, pp. 614–619 (2004)

    Google Scholar 

  11. Heikkilä, J., Silven, O.: A Four-step Camera Calibration Procedure with Implicit Image Correction. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1106–1112 (June 1997)

    Google Scholar 

  12. OpenCV Reference Manual v2.1, Open Source/Willow Garage (March 2010)

    Google Scholar 

  13. Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of Optical Flow Techniques. International Journal of Computer Vision 12, 43–77 (1994)

    CrossRef  Google Scholar 

  14. Thiemermann, S.: Direkte Mensch-Roboter-Kooperation in der Kleinteilmontage mit einem SCARA-Roboter. Dissertation, Faculty Mechanical Engineering – University Stuttgart (2005)

    Google Scholar 

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© 2012 Springer-Verlag Berlin Heidelberg

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Höcherl, J., Schlegl, T. (2012). An Image Based Algorithm to Safely Locate Human Extremities for Human-Robot Collaboration. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33515-0_17

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  • DOI: https://doi.org/10.1007/978-3-642-33515-0_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33514-3

  • Online ISBN: 978-3-642-33515-0

  • eBook Packages: Computer ScienceComputer Science (R0)