Advertisement

Grasping Control in Three-Fingered Robot Hand Teleoperation Using Desktop Haptic Device

  • Lingzhi Liu
  • Guanyang LiuEmail author
  • Yuru Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8619)

Abstract

This paper presents a three-fingered robot hand teleoperation system using desktop haptic device as the master manipulator. The grasp mapping and force feedback methods are developed for the system. Grasp forces of the robot hand are transformed to proper feedback force in master side. Operator controls the robot hand to grasp and hold different objects depending on the force feedback rather than visual feedback. We demonstrated that a wide range of objects, whose properties are well known by operator, were safely and stably grasped and the force based grasping control was more reliable than visual feedback based control. The intuitive and easy-to-realize system raises a new control scheme in robot hand teleoperation.

Keywords

Visual Feedback Force Feedback Haptic Device Master Manipulator Robot Hand 
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.

Notes

Acknowledgment

This research was supported by China domestic research project for International Thermonuclear Experimental Reactor (ITER) program under grant 2012GB102006, 2012GB102008 and supported by the Innovation Foundation of BUAA for PhD Graduates.

References

  1. 1.
    Yoshikawa, T.: Multi-fingered robot hands: control for grasping and manipulation. Ann. Rev. Control 34(2), 199–208 (2010)CrossRefGoogle Scholar
  2. 2.
    Okamura, A.M., Smaby, N., Cutkosk, M.R.: An overview of dexterous manipulation. In: Proceedings of 2000 IEEE International Conference on Robotic and Automation, vol. 1, pp. 255–262 (2000)Google Scholar
  3. 3.
    Pelossof, R., Miller, A., Allen, P., Jebara, T.: An SVM learning approach to robotic grasping. In: Proceedings of 2004 IEEE International Conference on Robotic and Automation, vol. 4, April 26–May 1, pp. 3512–3518 (2004)Google Scholar
  4. 4.
    Peer, A., Einenkel, S., Buss, M.: Multi-fingered telemanipulation - mapping of a human hand to a three finger gripper. In: Proceedings of the 17th IEEE International Symposium on Robot and Human Interactive Communication, 1–3 August 2008, pp. 465–470 (2008)Google Scholar
  5. 5.
    Geng, T., Lee, M., Hülse, M.: Transferring human grasping synergies to a robot. Mechatronics 21, 272–284 (2011)CrossRefGoogle Scholar
  6. 6.
    Blake, J., Gurocak, H.B..: Haptic glove with MR brakes for virtual reality. In: IEEE/ASME Trans. Mechatron. 14(5), 606–615 (2009)CrossRefGoogle Scholar
  7. 7.
    Lii, N.Y., Chen, Z., Pleintinger, B., Borst, C.H., Hirzinger, G., Schiele, A.: Toward understanding the effects of visual- and force-feedback on robotic hand grasping performance for space teleoperation. In: The 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, 18–22 October 2010, pp. 3745–3752 (2010)Google Scholar
  8. 8.
    Leeper, A., Chan, S., Hsiao, K., Ciocarlie, M., Salisbury, K.: Constraint-based haptic rendering of point data for teleoperated robot grasping. In: IEEE Haptics Symposium 2012, Vancouver, BC, Canada, 4–7 March 2012, pp. 377–383 (2012)Google Scholar
  9. 9.
    Westebring-van der Putten, E.P., van den Dobbelsteen, J.J., Goossens, R.H.M., Jakimowicz, J.J., Dankelman, J.: The effect of augmented feedback on grasp force in laparoscopic grasp control. IEEE Trans. Haptics 3(4), 280–291 (2010)CrossRefGoogle Scholar
  10. 10.
    Griffin, W.B., Provancher, W.R., Cutkosky, M.R.: Feedback strategies for telemanipulation with shared control of object handling forces. Presence 14(6), 720–731 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.State Key Lab of Virtual Reality Technology and SystemsBeihang UniversityBeijingChina

Personalised recommendations