Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-23T22:33:13.793Z Has data issue: false hasContentIssue false
  • English
  • Français

Improving transparency of virtual coupling for haptic interaction with human force observer

Published online by Cambridge University Press:  02 July 2015

Myungsin Kim  and
Dongjun Lee
Myungsin Kim
Affiliation:
Department of Mechanical and Aerospace Engineering and IAMD, Seoul National University, Seoul, 151-744, Republic of Korea. E-mail: [email protected]
Dongjun Lee*
Affiliation:
Department of Mechanical and Aerospace Engineering and IAMD, Seoul National University, Seoul, 151-744, Republic of Korea. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

Relying solely on virtual springs and dampers, the transparency of standard virtual coupling suffers from the device-proxy coordination error when a large interaction force is engaged (e.g., contact tasks) and also from the unmodifiable inertias of the haptic device and the virtual proxy. To overcome these limitations, we propose a novel virtual coupling scheme, which, utilizing passive decomposition and a human force observer, can maintain the device-proxy coordination error even during contact tasks, while also allowing for scaling down (or up) the apparent inertia of the coordinated device-proxy system, thereby, substantially improving transparency of the standard virtual coupling. Experiments are performed to show the performance and passivity of the proposed virtual coupling. Minimum-possible passive inertia scaling is also theoretically established via some positive-real analysis.

Keywords

Human force observerpassive decompositionpassivitytransparencyvirtual coupling
Type
Articles
Information
Robotica , Volume 35 , Issue 2 , February 2017 , pp. 354 - 369
Copyright
Copyright © Cambridge University Press 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Colgate, J. E., Stanley, M. C. and Brown, J. M., “Issues in the haptic display of tool use,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 3, Pittsburgh, PA, USA (1995) pp. 140–1995.Google Scholar
2. Adams, R. J. and Hannaford, B., “Stable haptic interaction with virtual environments,” IEEE Trans. Robot. Autom. 15 (3), 465–474 (1999).Google Scholar
3. Mitra, P. and Niemeyer, G., “Dynamic proxy objects in haptic simulations,” Proceedings of IEEE Conference on Robotics, Automation & Mechatronics, Barcelona, Spain (2004) pp. 1054–2004.Google Scholar
4. Zilles, C. B. and Salisbury, J. K., “A constraint-based god-object method for haptic display,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots & Systems 95. ‘Human Robot Interaction and Cooperative Robots’, vol. 3, Pittsburgh, USA (1995) pp. 146–1995.Google Scholar
5. Ortega, M., Redon, S. and Coquillart, S., “A six degree-of-freedom god-object method for haptic display of rigid bodies with surface properties,” IEEE Trans. Vis. Comput. Graph. 13 (3), 458–469 (2007).CrossRefGoogle ScholarPubMed
6. Yu, G., Wang, D. and Zhang, Y., “Accelerating optimization-based haptic rendering by parallel quadratic programming method,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots & Systems, Tokyo, Japan (2013) pp. 4499–2013.Google Scholar
7. Kolesnikov, M. and Zefran, M., “Energy-based 6-dof penetration depth computation for penalty-based haptic rendering algorithms,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots & Systems, San Diego, USA (2007) pp. 2120–2007.Google Scholar
8. Cirio, G., Marchal, M., Otaduy, M. A. and Lécuyer, A., “Six-dof haptic interaction with fluids, solids, and their transitions,” Proceedings of World Haptics Conference, IEEE, Daejeon, Korea (2013) pp. 157–162.Google Scholar
9. Lee, D. J., Kim, M. and Qiu, T., “Passive haptic rendering and control of lagrangian virtual proxy,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots & Systems, Algarve, Portugal (2012) pp. 64–2012.Google Scholar
10. Renz, M., Preusche, C., Pötke, M., Kriegel, H.-P. and Hirzinger, G., “Stable haptic interaction with virtual environments using an adapted voxmap-pointshell algorithm,” Proceedings of Eurohaptics. Citeseer, Birmingham, UK (2001) pp. 149–154.Google Scholar
11. Barbic, J. and James, D. L, “Six-dof haptic rendering of contact between geometrically complex reduced deformable models,” IEEE Trans. Haptics 1 (1), 39–52 (2008).CrossRefGoogle ScholarPubMed
12. Otaduy, M. A. and Lin, M. C., “A modular haptic rendering algorithm for stable and transparent 6-dof manipulation,” IEEE Trans. Robot. 22 (4), 751–762 (2006).Google Scholar
13. Duriez, C., Dubois, F., Kheddar, A. and Andriot, C., “Realistic haptic rendering of interacting deformable objects in virtual environments,” IEEE Trans. Vis. Comput. Graph. 12 (1), 36–47 (2006).Google Scholar
14. Huang, K. and Lee, D. J., “Consensus-based peer-to-peer control architecture for multiuser haptic interaction over the internet,” IEEE Trans. Robot. 29 (2), 417–431 (2013).Google Scholar
15. Sankaranarayanan, G. and Hannaford, B., “Experimental internet haptic collaboration using virtual coupling schemes,” Proceedings of the IEEE Symps. on Haptic Interfaces for Virtual Environments & Teleoperator Systems, Reno, NV, USA (2008) pp. 259–2008.Google Scholar
16. Lawrence, D. A., “Stability and transparency in bilateral teleoperation,” IEEE Trans. Robot. Autom. 9 (5), 624–637 (1993).CrossRefGoogle Scholar
17. Colgate, J. E. and Schenkel, G. G., “Passivity of a class of sampled-data systems: Application to haptic interfaces,” J. Robot. Syst. 14 (1), 37–47 (1997).Google Scholar
18. Lee, D. J., “Extension of Colgate's passivity condition for variable-rate haptics,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots & Systems, St. Louis, USA (2009) pp. 1761–2009.Google Scholar
19. Brown, J. M. and Colgate, J. E., “Minimum mass for haptic display simulations,” Proceedings of the ASME International Mechanical Engineering Congress and Exhibition, Anaheim, CA, USA (1998) pp. 249–1998.Google Scholar
20. Lee, D. J. and Huang, K., “On passive non-iterative varying-step numerical integration of mechanical systems for haptic rendering,” Proceedings of ASME Dynamic Systems & Control Conference, Ann Arbor, MI, USA (2008) pp. 1147–2008.Google Scholar
21. Lee, D. J. and Li, P. Y., “Passive bilateral control and tool dynamics rendering for nonlinear mechanical teleoperators,” IEEE Trans. Robot. 21 (5), 936–951 (2005).Google Scholar
22. Lee, D. J. and Li, P. Y., “Passive decomposition of mechanical systems with coordination requirement,” IEEE Trans. Autom. Control 58 (1), 230–235 (2013).CrossRefGoogle Scholar
23. Chen, W. H., Ballance, D. J., Gawthrop, P. J. and O'Reilly, J., “A nonlinear disturbance observer for robotic manipulators,” IEEE Trans. Indurstrial Electron. 47 (4), 932–938 (2000).Google Scholar
24. Gupta, A. and O'Malley, M. K., “Disturbance-observer-based force estimation for haptic feedback,” J. Dyn. Syst. Meas. Control 133 (1), 014505 (2011).Google Scholar
25. Slotine, J. J. E. and Li, W., Applied Nonlinear Control, vol. 199 (Prentice-Hall Englewood Cliffs, NJ, 1991).Google Scholar
26. Franken, M., Stramigioli, S., Misra, S., Secchi, C. and Macchelli, A., “Bilateral telemanipulation with time delays: A two-layer approach combining passivity and transparency,” IEEE Trans. Robot. 27 (4), 741–756 (2011).Google Scholar
27. Lee, D. J. and Huang, K., “Passive-set-position-modulation framework for interactive robotic systems,” IEEE Trans. Robot. 26 (2), 354–369 (2010).Google Scholar
28. Lee, D. J. and Spong, M. W., “Passive bilateral teleoperation with constant time delay,” IEEE 22 (2), 269–281 (2006).Google Scholar
29. Nuno, E., Ortega, R., Barabanov, N. E. and Basanez, L., “A globally stable pd-controller for bilateral teleoperators,” IEEE Trans. Robot. 24 (3), 753–758 (2008).Google Scholar
30. Kim, M. and Lee, D. J., “Toward transparent virtual coupling for haptic interaction during contact tasks,” Proceedings of World Haptics Conference, Daejeon, Korea (2013) pp. 163–2013.Google Scholar
31. Khatib, O., “A unified approach for motion and force control of robot manipulators: The operational space formulation,” IEEE J. Robot. Autom. RA–3 (1), 43–53 (1987).CrossRefGoogle Scholar
32. Spong, M. W., Hutchinson, S. and Vidyasaga, M., Robot Modeling and Control (John Wiley & Sons, Hoboken, NJ, 2006).Google Scholar
33. Brown, J. M. and Colgate, J. E., “Passive implementation of multibody simulations for haptic display,” Proceedings of ASME International Mechanical Engineering Congress & Exposition, Dallas, TX, USA (1997) pp. 85–1997.Google Scholar
34. Murray, R. M., Li, Z. and Sastry, S. S., A Mathematical Introduction to Robotic Manipulation (CRC, Boca Ranton, FL, 1993).Google Scholar
35. Daniel, R. W. and McAree, P. R., “Fundamental limits of performance for force reflecting teleoperation,” Int. J. Robot. Res. 8, 811–830 (1998).CrossRefGoogle Scholar
36. Buerger, S. P. and Hogan, N., “Complementary stability and loop shaping for improved human-robot interaction,” IEEE Trans. Robot. 23 (2), 232–244 (2007).Google Scholar
37. Iwasaki, T., Hara, S. and Yamauchi, H., “Dynamical system design from a control perspective: Finite frequency positive-realness approach,” IEEE Trans. Autom. Control 48 (8), 1337–1354 (2003).Google Scholar