Autonomous Object Handover Using Wrist Tactile Information

  • Jelizaveta KonstantinovaEmail author
  • Senka Krivic
  • Agostino Stilli
  • Justus Piater
  • Kaspar Althoefer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10454)


Grasping in an uncertain environment is a topic of great interest in robotics. In this paper we focus on the challenge of object handover capable of coping with a wide range of different and unspecified objects. Handover is the action of object passing an object from one agent to another. In this work handover is performed from human to robot. We present a robust method that relies only on the force information from the wrist and does not use any vision and tactile information from the fingers. By analyzing readings from a wrist force sensor, models of tactile response for receiving and releasing an object were identified and tested during validation experiments.



The research leading to these results has received funding from the European Community’s Seventh Framework Programme under grant agreement no. 610532, SQUIRREL, and from the European Unions Horizon 2020 research and innovation programme under grant agreement no. 287728, FourByThree.


  1. 1.
    Katz, D., Pyuro, Y., Brock, O.: Learning to manipulate articulated objects in unstructured environments using a grounded relational representation. In: Proceedings of Robotics: Science and Systems IV, Zurich, Switzerland, pp. 254–261, June 2008Google Scholar
  2. 2.
    Cotugno, G., Mohan, V., Althoefer, K., Nanayakkara, T.: Simplifying grasping complexity through generalization of kinaesthetically learned synergies. In 2014 IEEE International Conference on Robotics and Automation (ICRA), pp. 5345–5351, May 2014Google Scholar
  3. 3.
    Maurtua, I., Pedrocchi, N., Orlandini, A., de Gea Fernández, J., Vogel, C., Geenen, A., Althoefer, K., Shafti, A.: Fourbythree: imagine humans and robots working hand in hand. In: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA), pp. 1–8, September 2016Google Scholar
  4. 4.
    Edsinger, A., Kemp, C.C.: Human-robot interaction for cooperative manipulation: handing objects to one another. In: The 16th IEEE International Symposium on Robot and Human interactive Communication, RO-MAN 2007, pp. 1167–1172. IEEE (2007)Google Scholar
  5. 5.
    Huang, C.-M., Cakmak, M., Mutlu, B.: Adaptive coordination strategies for human-robot handovers. In: Robotics Science and Systems (2015)Google Scholar
  6. 6.
    Kupcsik, A., Hsu, D., Lee, W.S.: Learning dynamic robot-to-human object handover from human feedback. arXiv preprint arXiv:1603.06390 (2016)
  7. 7.
    Nagata, K., Oosaki, Y., Kakikura, M., Tsukune, H.: Delivery by hand between human and robot based on fingertip force-torque information. In Proceedings of 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems, Innovations in Theory, Practice and Applications (Cat. No.98CH36190), vol. 2, pp. 750–757, October 1998Google Scholar
  8. 8.
    Mellmann, H., Cotugno, G.: Dynamic motion control: Adaptive bimanual grasping for a humanoid robot. Fundamenta Informaticae 112(1), 89–101 (2011)Google Scholar
  9. 9.
    Sadigh, M.J., Ahmadi, H.: Robust control algorithm for safe grasping based on force sensing. In: 2008 IEEE International Conference on Robotics and Biomimetics, pp. 1279–1284, February 2009Google Scholar
  10. 10.
    Felip, J., Morales, A., Asfour, T.: Multi-sensor and prediction fusion for contact detection and localization. In: 2014 14th IEEE-RAS International Conference on Humanoid Robots (Humanoids), pp. 601–607. IEEE (2014)Google Scholar
  11. 11.
    Manuel, G.C., Grioli, G., Serio, A., Farnioli, E., Piazza, C., Bicchi, A.: Adaptive synergies for a humanoid robot hand. In: 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), Osaka, Japan, November 29–December 1, 2012, pp. 7–14 (2012)Google Scholar
  12. 12.
    Dai, J.S., Wang, D., Cui, L.: Orientation and workspace analysis of the multifingered metamorphic hand-metahand. IEEE Trans. Rob. 25(4), 942–947 (2009)CrossRefGoogle Scholar
  13. 13.
    Strabala, K., Lee, M.K., Dragan, A., Forlizzi, J., Srinivasa, S., Cakmak, M., Micelli, V.: Towards seamless human-robot handovers. J. Human-Robot Interact. (2013)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Jelizaveta Konstantinova
    • 1
    Email author
  • Senka Krivic
    • 2
  • Agostino Stilli
    • 3
  • Justus Piater
    • 2
  • Kaspar Althoefer
    • 1
  1. 1.School of Engineering and Material ScienceQueen Mary University of LondonLondonUK
  2. 2.Department of Computer ScienceUniversity of InnsbruckInnsbruckAustria
  3. 3.Department of InformaticsKing’s College LondonLondonUK

Personalised recommendations