Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-25T23:12:58.708Z Has data issue: false hasContentIssue false
  • English
  • Français

An automatic switching approach to teleoperation of mobile-manipulator systems using virtual fixtures

Published online by Cambridge University Press:  08 August 2016

M. R. Wrock  and
S. B. Nokleby
M. R. Wrock
Affiliation:
Mechatronic and Robotic Systems Laboratory, Institute of Technology, University of Ontario, Oshawa, Canada. E-mail: [email protected]
S. B. Nokleby*
Affiliation:
Mechatronic and Robotic Systems Laboratory, Institute of Technology, University of Ontario, Oshawa, Canada. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

This work presents a novel command strategy developed to improve operator performance and minimize difficulties in teleoperation tasks for mobile-manipulator systems with a holonomic base. Aimed specifically at novice operators, virtual fixtures are introduced as a means to minimize collisions and assist in navigation. Using the 6-degree-of-freedom (DOF) Omnibot mobile-manipulator system (MMS), a command strategy is implemented such that the operator need only control a 3-DOF haptic joystick to achieve full control of the Omnibot MMS. The command strategy is used to coordinate control between the arm and the base of the system, prevent collisions with known obstacles, and alert the operator of proximity to those obstacles with haptic forces. Through experimental testing it is shown that operator performance improved with the use of virtual fixtures.

Keywords

TeleoperationHapticsVirtual fixturesMobile manipulators
Type
Articles
Information
Robotica , Volume 35 , Issue 8 , August 2017 , pp. 1773 - 1792
Copyright
Copyright © Cambridge University Press 2016 

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. Wang, D., Yi, J., Zhao, D. and Yang, G., “Teleoperation System of the Internet-Based OmniDirectional Mobile Robot with a Mounted Manipulator,” Proceedings of the IEEE International Conference on Mechatronics and Automation, IEEE, Harbin, China, (2007) pp. 1799–1804.Google Scholar
2. Chui, C. K., Ong, J. S. K., Lian, Z. Y., Wang, Z. and Teo, J., “Haptics in Computer Mediated Simulation: Training in Vertebroplasty Surgery,” In: Simulation and Gaming, Vol. 37, No. 4, (2006) pp. 438–451.Google Scholar
3. Hvilshj, M. and Bgh, S., “Little helper - an autonomous industrial mobile manipulator concept,” Int. J. Adv. Robot. Syst. 8 (2), 80–90 (2011).Google Scholar
4. Kron, A., Schmidt, G., Petzold, B., Zah, M. I., Hinterseer, P. and Steinbach, E., “Disposal of Explosive Ordinances by Use of a Bimanual Haptic Telepresence System,” Proceedings of the International Conference on Robotics and Automation, IEEE, New Orleans, USA, Vol. 2 (2004) pp. 1968–1973.Google Scholar
5. Hirose, S. and Amano, S., “The Vuton: High Payload High Efficiency Holonomic Omni-Directional Vehicle,” Proceedings of the 6th International Symposium on Robotics Research, Hidden Valley, USA, (1993) pp. 253–260.Google Scholar
6. Palankar, M., De Laurentis, K. J., Alqasemi, R., Veras, E., Dubey, R. and Arbel, Y. D. E., “Control of a 9-dof Wheelchair-Mounted Robotic Arm System Using a p300 Brain Computer Interface: Initial Experiments,” Proceedings of the ROBIO 2008. IEEE International Conference on Robotics and Biomimetics, IEEE, Bangkok, Thailand, (2009) pp. 348–353.Google Scholar
7. Melchiorri, C., “Robotic Telemanipulation: An Introduction,” Winter School on Telesurgery, EURON Winter School on Telesurgery, Benidorm, Spain, (March 26–31, 2006).Google Scholar
8. Gunn, C. and Mettenmeyer, A., “Virtual Surgery Across the World,”. In CSIRO Media Release (2002).Google Scholar
9. Ise, Y. and Murakami, T., “An Approach to a Haptics System Control by Mobile Manipulator,” International Workshop on Advanced Motion Control, IEEE, Kawasaki, Japan (2004) pp. 239–242.Google Scholar
10. Yamanaka, E., Murakami, T. and Ohnishi, K., “Motion Control of Mobile Manipulator for Human Interaction,” Proceedings of the 28th Annual Conference of the Industrial Electronics Society. IECON 02, Sevilla, Spain, (2002) pp. 2785–2790.Google Scholar
11. Xin, L. et al., “Real-time obstacle avoidance for telerobotic systems based on equipotential surface,” Int. J. Adv. Robot. Syst. 9 (71) (2012) 8 pages.Google Scholar
12. Lim, D. and Seraji, H., “Configuration control of a mobile dexterous robot: Real-time implementation and experimentation,” Control, 16 (5), 601–618 (1993).Google Scholar
13. Shin, D. H., Hamner, B. S., Singh, S. and Hwangbo, M., “Motion Planning for a Mobile Manipulator with Imprecise Locomotion,” Proceedings of the International Conference on Intelligent Robots and Systems, IEEE/RSJ, Las Vegas, USA, (2003) pp. 847–853.Google Scholar
14. Chung, J. H., Velinsky, S. A. and Hess, R. A., “Interaction control of a redundant mobile manipulator,” Int. J. Robot. Res. 26 (1), 1302–1309 (1998).Google Scholar
15. Nath, N., Tatlicioglu, E. and Dawson, D. M., “Teleoperation with kinematically redundant robot manipulators with sub-task objectives,” Robotica 27 (07), 1027–1038 (2009).CrossRefGoogle Scholar
16. Seraji, H., “Configuration control of redundant manipulators: Theory and implementation,” Trans. Robot. Autom. IEEE, 5 (4), 472–490 (1989).Google Scholar
17. Pin, F. G. and Culioli, J. C., “Optimal positioning of combine mobila platform manipulator systems for material handling tasks,” J. Int. Robot. Syst. 6 (2), 165–182 (1992).Google Scholar
18. Whitney, D. E., “Resolved motion rate control of manipulators and human protheses,” IEEE Trans. Man-Mach. Syst. 10 (2), 47–53 (1969).Google Scholar
19. Shamir, T. and Yomdin, Y., “Repeatability of redundant manipulators: Mathematical solution of the problem,” IEEE Trans. Autom. Control, 33 (11), 1004–1008 (1983).Google Scholar
20. Sciavicco, L. and Siciliano, B., “A solution algorithm to the inverse kinematic problem for redundant manipulators,” IEEE J. Robot. Autom. 4 (4), 403–410 (1988).CrossRefGoogle Scholar
21. Sciavicco, L. and Siciliano, B., “Solving the Inverse Kinematic Problem for Robotic Manipulators,” Proceedings of the 6th CISM-IFToMM Symposium Theory and Practice of Robots and Manipulators, Krakow, Poland, (1987) pp. 107–114.Google Scholar
22. Baillieul, J., “Kinematic Programming Alternatives for Redundant Manipulators,” Proceedings of the IEEE International Conference on Robotics and Automation, St. Louis, USA, (1985) pp. 722–728.Google Scholar
23. Baillieul, J., “Avoiding Obstacles and Resolving Kinematic Redundancy,” Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, USA, (1986) pp. 1698–1704.Google Scholar
24. Nakamur, H. H. Y. and Yoshikawa, T., “Task-priority based redundancy control of robot manipulators,” Int. J. Robot. Res. 6 (2), 3–15 (1987).CrossRefGoogle Scholar
25. Klein, C. A. and Huang, C. H., “Review of pseudoinverse control for use with kinematically redundant manipulators,” IEEE Trans. Syst. Man Cybernet. SMC–13 (2), 245–250 (1983).Google Scholar
26. Zhang, H., Jia, Y., Guo, Y., Qian, K., Song, A. and Xi, N., “Online sensor information and redundancy resolution based obstacle avoidance for high dof mobile manipulator teleoperation,” Int. J. Adv. Robot. Syst. 10 (244) (2013).CrossRefGoogle Scholar
27. X, P., et al., “Operation modes and control schemes for a telerobot with time delay,” Int. J. Adv. Robot. Syst. 9 (57) (2012).Google Scholar
28. Li, H. et al., “Virtual-environment modeling and correction for force-reflecting teleoperation with time delay,” IEEE Trans. Indust. Electron. 54 (2), 1227–1233 (2007).Google Scholar
29. Ghao, C., Zhang, M. and Sun, L., “Motion Planning and Coordinated Control for Mobile Manipulators,” Proceedings of the 9th International Conference on Control, Automation, Robotics and Vision, Singapore (2006) 6 pages.Google Scholar
30. Lin, S. and Goldenberg, A. A., “Neural-network control of mobile manipulators,” Trans. Neural Netw. IEEE 12 (5), 1121–1133 (2001).Google Scholar
31. Chen, M. W. and , Zalzala, “Neural network based motion control and applications to non-holonomic mobile manipulators,” Top. Artif.Intell. PRICAI, 1531, 353–364 (1998).Google Scholar
32. Soylu, S., Firmani, F., Buckham, B. and Podhorodeski, R. P., “Comprehensive Underwater Vehicle-Manipulator System Teleoperation,” Proceedings of OCEANS '10, Seattle, USA, (2010) 6 pages.Google Scholar
33. Hung, N., Kim, D., Kim, H. and Kim, S., “Tracking controller design of omnidirectional mobile manipulator system,” Proceedings of ICCAS-SICE, Fukuoka, Japan, (2009) pp. 539–544.Google Scholar
34. Watanabe, K., Sato, K., Izumi, K. and Kunitake, Y., “Analysis and control for an omnidirectional mobile manipulator,” J. Int. Robot. Syst. 27 (1), 3–20 (2000).Google Scholar
35. Takubo, T., Arai, H. and Tanie, K., “Control of mobile manipulator using a virtual impedance wall” Proceedings of IEEE International Conference on Robotics and Automation, Washington DC, USA, (2002) pp. 3571–3576.Google Scholar
36. Frejek, M. and Nokleby, S. B., “A methodology for tele-operating mobile manipulators with an emphasis on operator ease of use,” Robotica 31 (3), 331–344 (2013).Google Scholar
37. Lizarralde, F. and Wen, J. T., “Quaternion-Based Coordinated Control of a Subsea Mobile Manipulatior with Only Position Measurements,” Proceedings of the 34th Conference on Decision and Control, New Orleans, USA, (1995) pp. 3396–4001.Google Scholar
38. Qian, K., Song, A., Bao, J. and Zhang, H., “Small teleoperated robot for nuclear radiation and chemical leak detection. Int. J. Adv. Robot. Syst. 9 (70) (2012).Google Scholar
39. Wrock, M. R. and Nokleby, S. B., “Haptic Teleoperation of a Manipulator using Virtual Fixtures and Hybrid Position-Velocity Control,” Proceedings of 13th World Congress in Mechanism and Machine Science, Guanajuato, Mexico (2011) 6 pages.Google Scholar
40. Wrock, M. R. and Nokleby, S. B., “Command Strategies for Tele-Operation of Mobile-Manipulator Systems Via a Haptic Input Device,” Proceedings of the ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, ASME/IEEE, Washington DC, USA, (2011) pp. 623–630.Google Scholar
41. Wrock, M. and Nokleby, S., “Decoupled Teleoperation of a Holonomic Mobile-Manipulator System using Automatic Switching,” Proceedings of the Electrical and Computer Engineering (CCECE), 2011 24th Canadian Conference on, Niagara Falls, Canada, (2011) pp. 001164–001168.Google Scholar
42. Wrock, M. and Nokleby, S. “Virtual Fixtures and Automatic Mode Switching for Teleoperation Tasks,” Proceedings of the ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Chicago, USA, (2012) pp. 745–751.Google Scholar
43. Farkhatdinov, I., “Switching of Control Signals in Teleoperation Systems: Formalization and Application,” Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Xi'an, China, (2008) pp. 353–358.Google Scholar
44. Liu, B. L., Yuan, M., Chen, G. and Peng, J., “Spatial motion constraints using flexible virtual fixtures,” Appl. Mech. Mater. 427, 24–28 (2013).Google Scholar
45. Bemis, S. and Nokleby, S. B., “Design of an Omnibot Autonomous Vehicle,” Proceedings of the 2008 CSME Forum, Ottawa, Canada, (2008) 6 pages.Google Scholar
46. Ginzburg, S. and Nokleby, S. B., “Indoor localization of an omni-directional wheeled mobile robot,” Trans. Can. Soc. Mech. Eng. 36 (4), 1043–1056 (2013).CrossRefGoogle Scholar