Hostname: page-component-76d6cb85b7-7262s Total loading time: 0 Render date: 2026-07-21T05:16:09.261Z Has data issue: false hasContentIssue false
  • English
  • Français

Toward safe and stable time-delayed mobile robot teleoperation through sampling-based path planning

Published online by Cambridge University Press:  11 July 2011

Jorge Nieto ,
Emanuel Slawiñski ,
Vicente Mut  and
Bernardo Wagner
Jorge Nieto*
Affiliation:
Real-Time Systems Group, Leibniz Universität Hannover, D-30167, Germany Instituto de Automática, Universidad Nacional de San Juan, J5400ARL, Argentina
Emanuel Slawiñski
Affiliation:
Instituto de Automática, Universidad Nacional de San Juan, J5400ARL, Argentina
Vicente Mut
Affiliation:
Instituto de Automática, Universidad Nacional de San Juan, J5400ARL, Argentina
Bernardo Wagner
Affiliation:
Real-Time Systems Group, Leibniz Universität Hannover, D-30167, Germany
*
*Corresponding author. E-mail: nieto@rts.uni-hannover.de
Get access Rights & Permissions [Opens in a new window]

Summary

This work proposes a teleoperation architecture for mobile robots in partially unknown environments under the presence of variable time delay. The system is provided with artificial intelligence represented by a probabilistic path planner that, in combination with a prediction module, assists the operator while guaranteeing a collision-free motion. For this purpose, a certain level of autonomy is given to the system. The structure was tested in indoor environments for different kinds of operators. A maximum time delay of 2s was successfully coped with.

Keywords

Mobile robotsTime-delayed teleoperationPath planningSupervisory controlHuman operator

Information

Type
Articles
Information
Robotica , Volume 30 , Issue 3 , May 2012 , pp. 351 - 361
Copyright
Copyright © Cambridge University Press 2011

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.)

Article purchase

Temporarily unavailable

References

1.Aldrich, J., “Correlations genuine and spurious in pearson and yule,” Stat. Sci. 10 (4), 364–376 (1995).Google Scholar
2.Aicardi, M., Casalino, G., Bicchi, A. and Balestrino, A., “Closed loop steering of unicycle-like vehicles via Lyapunov techniques,” IEEE Robot. Autom. Mag. 2, 27–35 (1995).Google Scholar
3.Anderson, R. J. and Spong, M., “Bilateral control of teleoperators with time delay,” IEEE Trans. Autom. Control 34 (5), 494–501 (1989).Google Scholar
4.Bejczy, A. K., Kim, W. S. and Venema, S. C., “The Phantom Robot: Predictive Displays for Teleoperation with Time Delay,” Proceedings of the IEEE International Conference on Robotics and Automation, Cincinnati, OH, USA (1990) pp. 546–551.Google Scholar
5.Brady, K. and Tarn, T. J., “Internet-Based Teleoperation,” Proceedings of the 2001 IEEE International Conference on Robotics and Automation, Seoul, Korea (2000) pp. 644–649.Google Scholar
6.Elhajj, I., Xi, Ni., Fung, W. K., Liu, Y. H., Hasegawa, Y. and Fukuda, T., “Supermedia-enhanced internet-based telerobotics,” Proc. IEEE. 91 (3), 396–421 (2003).Google Scholar
7.Ferguson, D., Kalra, N. and Stentz, A., “Replanning with RRTs,” Proceedings of the IEEE International Conference on Robotics and Automation, Orlando, FL, USA (2006) pp. 1243–1248.Google Scholar
8.Funda, J. and Paul, R. P., “Teleprogramming: Toward delay-invariant remote manipulation,” Presence: Teleop. Virt. Environ. 1 (1), 29–44 (1992).Google Scholar
9.Hernando, M. and Gambao, E., “A Robot Teleprogramming Architecture,” Proceedings of the International Conference on Advanced Intelligent Mechatronics, Kobe, Japan (2003) pp. 1113–1118.Google Scholar
10.Hokayem, P. F. and Spong, M. W., “Bilateral tele-operation: An historical survey,” Autom. 42 (12), 2035–2057 (2006).Google Scholar
11.Kavraki, L. E., Svetska, P., Latombe, J. C. and Overmars, M., “Probabilistic roadmaps for path planning in high-dimensional configuration spaces,” IEEE Trans. Robot. Autom. 12 (4), 566–580 (1996).Google Scholar
12.Kikuchi, J., Takeo, K. and Kosuge, K., “Teleoperation System via Computer Network for Dynamic Environment,” Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium (1998) pp. 3534–3539.Google Scholar
13.Kim, W., Hannaford, B. and Bejczy, A., “Force reflection and shared compliant control in operating telemanipulators with time delay,” IEEE Trans. Robot. Autom. 8 (2), 176–185 (1992).Google Scholar
14.LaValle, S. M., “Rapidly-Exploring Random Trees: A New Tool for Path Planning,” Technical Report No., 98–11. Computer Science Department, Iowa State University (1998).Google Scholar
15.LaValle, S. M., Planning Algorithms (Cambridge University Press, Cambridge, MA, USA, 2006).Google Scholar
16.Lawrence, D. A., “Stability and transparency in bilateral teleoperation,” IEEE Trans. Robot. Autom. 9 (5), 624–637 (1993).Google Scholar
17.Lee, D. J., Martinez-Palafox, O. and Spong, M. W., “Bilateral Teleoperation of a Wheeled Mobile Robot over Delayed Communication Networks,” Proceedings of IEEE International Conference on Robotics and Automation, Orlando, FL, USA (2006) pp. 3298–3303.Google Scholar
18.Niemeyer, G. and Slotine, J. J. E., “Stable adaptive teleoperation,” IEEE J. Ocean. Eng. 16 (1), 152–162 (1991).Google Scholar
19.Nieto, J., Slawiñski, E., Mut, V. and Wagner, B., “Online Path Planning Based on Rapidly-Exploring Random Trees,” Proceedings of IEEE, International Conference on Industrial Technology, Valparaiso, Chile (2010) pp. 1431–1436.Google Scholar
20.Nieto, J., Slawiñski, E., Mut, V. and Wagner, B., “Mobile Robot Teleoperation Augmented with Prediction and Path-Planning,” Proceedings of the International Symposium on Analysis, Design and Evaluation of Human-Machine Systems (IFAC-HMS '10), Valenciennes, France (Aug. 31–Sep. 3, 2010).Google Scholar
21.Park, J. H. and Cho, H. C., “Sliding-Mode Control of Bilateral Teleoperation Systems with Force-Reflection on the Internet,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Takamatsu, Japan (2000) pp. 1187–1192.Google Scholar
22.Sheridan, T. B., Telerobotics, Automation, and Human Supervisory Control (The MIT Press, Cambrige, MA, USA, 1992).Google Scholar
23.Sheridan, T. B., “Teleoperation, telerobotics and telepresence: A progress report,” Control Eng. Pract. 3 (2), 205–214 (1995).Google Scholar
24.Slawiñski, E., Mut, V. and Postigo, J., “Teleoperation of mobile robots with time-varying delay,” IEEE Trans. Robot. 23 (5), 1071–1082 (2007).Google Scholar
25.Slawiñski, E. and Mut, V., “Control using prediction for teleoperation of mobile robots,” Proceedings of the IEEE International Conference on Mechatronics and Automation, Harbin, China (2007) pp. 1172–1787.Google Scholar
26.Slawiñski, E. and Mut, V., “Control scheme including prediction and augmented reality for teleoperation of mobile robots,” Robotica 28 (1), 11–22 (2010).Google Scholar
27.Staal, M., “Stress, Cognition, and Human Performance: A Literature Review and Conceptual Framework,” NASA TM 2004-212824 [Online] 2004, http://human-factors.arc.nasa.gov/flightcognition/Publications/IH_054_Staal.pdf. (accessed Jul 8, 2010).Google Scholar
28.Carelli, R., Secchi, H. and Mut, V., “Algorithms for stable control of mobile robots with obstacle avoidance,” Latin Am. Appl. Res. 29 (2–3), 191–196 (1999).Google Scholar