Advertisement

Increasing Flexibility of Mobile Manipulation and Intuitive Human-Robot Interaction in RoboCup@Home

  • Jörg Stückler
  • David Droeschel
  • Kathrin Gräve
  • Dirk Holz
  • Michael Schreiber
  • Angeliki Topalidou-Kyniazopoulou
  • Max Schwarz
  • Sven Behnke
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8371)

Abstract

In this paper, we describe system and approaches of our team NimbRo@Home that won the RoboCup@Home competition 2013. We designed a multi-purpose gripper for grasping typical household objects in pick-and-place tasks and also for using tools. The tools are complementarily equipped with special handles that establish form closure with the gripper, which resists wrenches in any direction. We demonstrate tool use for opening a bottle and grasping sausages with a pair of tongs in a barbecue scenario. We also devised efficient deformable registration methods for the transfer of manipulation skills between objects of the same kind but with differing shape. Finally, we enhance human-robot interaction with a remote user interface for handheld PCs that enables a user to control capabilities of the robot. These capabilities have been demonstrated in the open challenges of the competition. We also explain our approaches to the predefined tests of the competition, and report on the performance of our robots at RoboCup 2013.

Keywords

Service Robot Deformable Registration Monte Carlo Localization Indoor Navigation Manipulation Skill 
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.

References

  1. 1.
    van der Zant, T., Wisspeintner, T.: RoboCup X: A proposal for a new league where RoboCup goes real world. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, pp. 166–172. Springer, Heidelberg (2006)Google Scholar
  2. 2.
    Wisspeintner, T., van der Zant, T., Iocchi, L., Schiffer, S.: RoboCup@Home: Scientific competition and benchmarking for domestic service robots. Interaction Studies 10(3), 393–428 (2009)CrossRefGoogle Scholar
  3. 3.
    Elara, M.R., Holz, D., Iocchi, L., Mahmoudi, F., del Solar, J.R., Stückler, J., Sugiura, K., Wachsmuth, S., Xie, J., van der Zant, T.: RoboCup@Home: Rules & regulations (2013), http://www.robocupathome.org/rules
  4. 4.
    Stückler, J., et al.: NimbRo@Home: Winning team of the RoboCup@Home competition 2012. In: Chen, X., Stone, P., Sucar, L.E., van der Zant, T. (eds.) RoboCup 2012. LNCS (LNAI), vol. 7500, pp. 94–105. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  5. 5.
    Grisetti, G., Stachniss, C., Burgard, W.: Improved techniques for grid mapping with Rao-Blackwellized particle filters. IEEE Trans. on Rob. 23(1), 34–46 (2007)CrossRefGoogle Scholar
  6. 6.
    Fox, D.: KLD-sampling: Adaptive particle filters and mobile robot localization. In: Advances in Neural Information Processing Systems (NIPS), pp. 26–32 (2001)Google Scholar
  7. 7.
    Stückler, J., Steffens, R., Holz, D., Behnke, S.: Efficient 3D object perception and grasp planning for mobile manipulation in domestic environments. In: Robotics and Autonomous Systems (2012)Google Scholar
  8. 8.
    Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Computer Vision and Image Understanding 110(3), 346–359 (2008)CrossRefGoogle Scholar
  9. 9.
    Myronenko, A., Song, X.: Point set registration: Coherent point drift. IEEE Trans. on PAMI 32(12), 2262–2275 (2010)CrossRefGoogle Scholar
  10. 10.
    Stückler, J., Behnke, S.: Multi-resolution surfel maps for efficient dense 3D modeling and tracking. Visual Communication and Image Representation (2013)Google Scholar
  11. 11.
    Stückler, J., Behnke, S.: Efficient deformable registration of multi-resolution surfel maps for object manipulation skill transfer. In: IEEE International Conference on Robotics and Automation, ICRA (2014)Google Scholar
  12. 12.
    Droeschel, D., Stückler, J., Behnke, S.: Learning to interpret pointing gestures with a time-of-flight camera. In: Proceedings of the 6th ACM International Conference on Human-Robot Interaction, HRI (2011)Google Scholar
  13. 13.
    Stückler, J., Behnke, S.: Following human guidance to cooperatively carry a large object. In: Proceedings of the 11th IEEE-RAS International Conference on Humanoid Robots (Humanoids), pp. 218–223 (2011)Google Scholar
  14. 14.
    Stückler, J., Behnke, S.: Compliant task-space control with back-drivable servo actuators. In: Röfer, T., Mayer, N.M., Savage, J., Saranlı, U. (eds.) RoboCup 2011. LNCS, vol. 7416, pp. 78–89. Springer, Heidelberg (2012)Google Scholar
  15. 15.
    Muszynski, S., Stückler, J., Behnke, S.: Adjustable autonomy for mobile teleoperation of personal service robots. In: Proc. of the IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN (2012)Google Scholar
  16. 16.
    Schwarz, M., Stückler, J., Behnke, S.: Mobile teleoperation interfaces with adjustable autonomy for personal service robots. In: 9th ACM/IEEE International Conference on Human-Robot Interaction, HRI (2014)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Jörg Stückler
    • 1
  • David Droeschel
    • 1
  • Kathrin Gräve
    • 1
  • Dirk Holz
    • 1
  • Michael Schreiber
    • 1
  • Angeliki Topalidou-Kyniazopoulou
    • 1
  • Max Schwarz
    • 1
  • Sven Behnke
    • 1
  1. 1.Computer Science Institute VI: Autonomous Intelligent SystemsRheinische Friedrich-Wilhelms-Universität BonnBonnGermany

Personalised recommendations