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Force Reflecting Teleoperation Via IPv6 Protocol with Geometric Constraints Haptic Guidance

  • Emmanuel Nuño
  • Adolfo Rodríguez
  • Luis Basañez
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 31)

Summary

When dealing with teleoperated systems, several important aspects have to be considered: unstructured environment, communication delay, human operator uncertainty, and safety at the remote site, amongst others. The main contribution of this work, that tackles some of the aforementioned issues, is a system that combines a force feedback teleoperation scheme with geometric constraints and haptic guidance. The allowed motion space of a robot can be reduced by specifying a set of geometric relations between the robot tool and the workcell’s fixed objects. These relations are processed by a geometric reasoning module that generates a compatible motion subspace. Restriction forces are then fed to the operator via a haptic interface in order to guide its movements inside this subspace. The communication channel between the local center and the remote cell is implemented using high speed networks with the novel IPv6 protocol. The slave robot control is based on position or velocity. Experimental results validate the proposed approach.

Keywords

Viscous Force Geometric Constraint Force Feedback Haptic Device Input Constraint 
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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References

  1. 1.
    B.J. Unger, A. Nicolaidis, P.J. Berkelman, A. Thompson, S. Lederman, R.L. Klatzky, and R.L. Hollis. Virtual peg-in-hole performance using a 6-dof magnetic levitation haptic device: comparison with real forces and with visual guidance alone. In Proceedings of the 10th IEEE Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, pages 263–270, March 2002.Google Scholar
  2. 2.
    S. Shon and S. McMains. Evaluation of drawing on 3d surfaces with haptics. In IEEE Computer Graphics and Applications, 24(6):40–50, Nov.–Dec. 2004.CrossRefGoogle Scholar
  3. 3.
    T.H. Massie and J.K. Salisbury. The phantom haptic interface: A device for probing virtual objects. In Proceedings of the ASME Winter Annual Meeting, Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 55(1):295–300, Nov. 1994.Google Scholar
  4. 4.
    N. Turro, O. Khatib, and E. Coste-Maniere. Haptically augmented teleoperation. In Proceedings of the IEEE International Conference on Robotics and Automation, 1:386–392, May 2001.Google Scholar
  5. 5.
    A. Casavola and M. Sorbara. Towards constrained teleoperation for safe long-distance robotic surgical operations. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 697–702, 2005.Google Scholar
  6. 6.
    N. Diolaiti, G. Niemeyer, F. Barbagli, J.K. Salisbury, and C. Melchiorri. The effect of quantization and coulomb friction on the stability of haptic rendering. In First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, pages 237–246, March 2005.Google Scholar
  7. 7.
    J.E. Colgate, P.E. Grafing, M.C. Stanley, and G. Schenkel. Implementation of stiff virtual walls in force-reflecting interfaces. In Proceedings of the IEEE Virtual Reality Annual International Symposium, pages 202–208, 1993.Google Scholar
  8. 8.
    P. Pan, K.M. Lynch, M.A. Peshkin, and J.E. Colgate. Static single-arm force generation with kinematic constraints. In Proceedings of the IEEE International Conference on Robotics and Automation, 3:2794–2800, 2004.Google Scholar
  9. 9.
    T. Tickel, D. Hannon, K.M. Lynch, M.A. Peshkin, and J.E. Colgate. Kinematic constraints for assisted single-arm manipulation. In Proceedings of the IEEE International Conference on Robotics and Automation, 2:2034–2041, 2002.Google Scholar
  10. 10.
    E.S. Boy, E. Burdet, C.L. Teo, and Colgate. Motion guidance experiments with scooter cobot. In Proceedings of the 11th IEEE Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, 20(4):63–69, March 2003.CrossRefGoogle Scholar
  11. 11.
    E.B. Fgee, J.D. Kenney, W.J. Phillips, W. Robertson, and S. Sivakumar. Comparison of qos performance between ipv6 qos management model and intserv and diffserv qos models. In Proceedings of the 3rd IEEE Annual Communication Networks and Services Research Conference, pages 287–292, May 2005.Google Scholar
  12. 12.
    IPv6. Ipv6 information page. http://www.ipv6.org/, 2005.Google Scholar
  13. 13.
    V. Srivastava, C. Wargo, and S. Lai. Aviation application over ipv6: performance issues. In Proceedings of the 2004 IEEE Aerospace Conference, 3:1661–1670, March 2004.Google Scholar
  14. 14.
    P.X. Liu, M. Meng, and S. Yang. Data communications for internet robots. Kluwer Academic Autonomous Robots, 15(3):213–223, 2003.CrossRefGoogle Scholar
  15. 15.
    R. Oboe. Web-interfaced, force-reflecting teleoperation systems. IEEE Transactions on Industrial Electronics, 48(3):1257–1265, Dec. 2001.CrossRefGoogle Scholar
  16. 16.
    S. Munir and W.J. Book. Internet-based teleoperation using wave variables with prediction. IEEE/ASME Transactions on Mechatronics, 7(2):124–133, June 2002.CrossRefGoogle Scholar
  17. 17.
    P.X. Liu, M. Meng, Y. Xiufen, and J. Gu. An UDP-based protocol for internet robots. In Proceedings of the IEEE 4th World Congress on Intelligent Control and Automation, 1:59–65, June 2002.CrossRefGoogle Scholar
  18. 18.
    R. Safaric, S. Sinjur, B. Zalik, and R.M. Parkin. Control of robot arm with virtual environment via the internet. In Proceedings of the IEEE, 91(3):422–429, March 2003.CrossRefGoogle Scholar
  19. 19.
    K. Taylor and B. Dalton. Internet robots: a new robotics niche. IEEE Robotics & Automation Magazine, 7(1):27–34, March 2000.CrossRefGoogle Scholar
  20. 20.
    R.C. Luo, K.L. Su, S.H. Shen, and K.H Tsai. Networked intelligent robots through the internet: issues and opportunities. In Proceedings of the IEEE, 91(3):371–382, March 2003.CrossRefGoogle Scholar
  21. 21.
    C.M. Hoffman and R. Joan-Arinyo. A brief on constraint solving. Unabridged version at http://www.cs.purdue.edu/homes/cmh/distribution/papers/Constraints/ThailandFull.pdf; abridged version to appear in CAD&A, pages 873–881, 2005.Google Scholar
  22. 22.
    E. Celaya. LMF: A program for positioning objects using geometrical relationships. In VII International Conference on Applications of Artificial Intelligence in Engineering. Elsevier Applied Science, pages 873–881, 1992.Google Scholar
  23. 23.
    F. Janabi-Sharifi, V. Hayward, and C-S.J Chen. Discrete-time adaptive windowing for velocity estimation. Control Systems Technology, IEEE Transactions on, 8(6):1003–1009, Nov. 2000.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Emmanuel Nuño
    • 1
  • Adolfo Rodríguez
    • 1
  • Luis Basañez
    • 1
  1. 1.Institute of Industrial and Control EngineeringTechnical University of Catalonia (UPC)BarcelonaSpain

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