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A Methodology for tele-operating mobile manipulators with an emphasis on operator ease of use

Published online by Cambridge University Press:  07 June 2012

M. Frejek  and
S. B. Nokleby
M. Frejek
Affiliation:
University of Ontario Institute of Technology Oshawa, Ontario, Canada
S. B. Nokleby*
Affiliation:
University of Ontario Institute of Technology Oshawa, Ontario, Canada
*
*Corresponding author. E-mail: scott.nokleby@uoit.ca
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Summary

An algorithm for the tele-operation of mobile-manipulator systems with a focus on ease of use for the operator is presented. The algorithm allows for unified, intuitive, and coordinated control of mobile manipulators. It consists of three states. In the first state, a single 6-degrees-of-freedom (DOF) joystick is used to control the manipulator's position and orientation. The second state occurs when the manipulator approaches a singular configuration, resulting in the mobile base moving in a manner so as to keep the end-effector travelling in its last direction of motion. This is done through the use of a constrained optimization routine. The third state is entered when the operator returns the joystick to the home position. Both the mobile base and manipulator move with respect to one another keeping the end-effector stationary and placing the manipulator into an ideal configuration. The algorithm has been implemented on an 8-DOF mobile manipulator and the test results show that it is effective at moving the system in an intuitive manner.

Keywords

Mobile manipulatorTele-operationOptimizationEase of use
Type
Articles
Information
Robotica , Volume 31 , Issue 3 , May 2013 , pp. 331 - 344
Copyright
Copyright © Cambridge University Press 2012

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References

1.Tchoń, K. and Malek, Ł., Advances in Robot Kinematics: Analysis and Design, (Lenarčič, J. and Wenger, P., eds.) (Springer Netherlands) ch. 3, pp. 155–164.Google Scholar
2.Seraji, H., “An On-Line Approach to Coordinated Mobility and Manipulation,” In: Proceedings of the 1993 IEEE International Conference on Robotics and Automation, Atlanta, GA (May 1993), vol. 1, pp. 28–35.Google Scholar
3.Seraji, H., “A unified approach to motion control of mobile manipulators,” The Int. J. Robot. Res. 17 (2), 107–118 (1998).CrossRefGoogle Scholar
4.Fourquet, J. Y. and Renaud, M., Experimental Robotics VI, (Corke, P. and Trevelyan, J., eds.) (Springer Berlin/Heidelberg) vol. 250, ch. 4, pp. 139–149.Google Scholar
5.Dai, L. and Li, Z., “Design and Implementation of Motion Control for Teleoperated Mobile Manipulators,” In: Proceedings of the 8th World Congress on Intelligent Control and Automation, Jinan, China (July 2010) pp. 6691–6696.Google Scholar
6.Wang, C. C. and Kumar, V., “Velocity Control of Mobile Manipulators,” In: Proceedings of the 1993 IEEE International Conference on Robotics and Automation, Atlanta, GA (May 1993), vol. 2, pp. 713–718.Google Scholar
7.Tan, J., Xi, N. and Wang, Y., “Integrated task planning and control for mobile manipulators,” Int. J. Robot. Res. 22 (5), 337–354 (2003).CrossRefGoogle Scholar
8.Takubo, T., Arai, H. and Tanie, K., “Control of Mobile Manipultor Using a Virtual Impedance Wall,” In: Proceedings of the 2002 IEEE International Conference on Robotics & Automation, Washington, DC (2002) pp. 3571–3576.Google Scholar
9.Anderson, D., Howard, T., Apfelbaum, D., Herman, H. and Kelly, A., “Coordinated Control and Range Imaging for Mobile Manipulation,” Proceedings of the 11th International Symposium on Experimental Robotics (ISER '08), Athens, Greece (2008).Google Scholar
10.Shin, D. H., Hamner, B. S., Singh, S. and Hwangbo, M., “Motion Planning for a Mobile Manipulator with Imprecise Locomotoin,” In: Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, Nevada (2003) pp. 847–853.Google Scholar
11.Hentout, A., Bouzouia, B., Akli, I., Ouzzane, E., Benbouali, R. and Bouskia, M. A., “Multi-Agent Control Architecture of Mobile Manipulators: Following an Operational Trajectory,” In: Proceedings of the 2009 International Conference on Signals, Circuits and Systems, Medenine, Tunisia (Nov. 2009) pp. 1–6.Google Scholar
12.Huang, Q., Tanie, K. and Sugano, S., “Coordinated motion planning for a mobile manipulator considering stability and manipulation,” Int. J. Robot. Res. 19 (8), 732–742 (2000).CrossRefGoogle Scholar
13.Pin, F. G. and Culioli, J. C., “Optimal positioning of combined mobile platform-manipulator systems for material handling tasks,” J. Intell. Robot. Syst. 6 (2), 165–182 (1992).CrossRefGoogle Scholar
14.Gao, 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).Google Scholar
15.Lin, S. and Goldenberg, A. A., “Neural-network control of mobile manipulators,” IEEE Trans. Neural Netw. 12 (5), 1121–1133 (2001).Google ScholarPubMed
16.Chen, M. W. and Zalzala, A. M. S., “Neural Network Based Motion Control and Applications to Non-holonomic Mobile Manipulators,” In: Proceedings of The Pacific Rim International Conference on Artificial Intelligence (PRICAI '98), Singapore (Nov. 22-27, 1998), pp. 353–364.Google Scholar
17.Antonelli, G. and Chiaverini, S., “Task-Priority Redundancy Resolution for Underwater Vehicle-Manipulator Systems,” In: Proceedings of the 1998 IEEE International Conference on Robotics & Automation, Leuven, Belgium (1998) pp. 768–773.Google Scholar
18.Antonelli, G. and Chiaverini, S., “Fuzzy redundancy resolution and motion coordination for underwater vehicle-manipulator systems,” IEEE Trans. Fuzzy Syst. 11 (1), 109–120 (2003).CrossRefGoogle Scholar
19.Nagatani, K. and Yuta, S., “Door-Opening Behavior of an Autonomous Mobile Manipulator by Sequence of Action Primitives,” J. Robot. Syst. 13 (11), 709–721 (1996).3.0.CO;2-Z>CrossRefGoogle Scholar
20.Mbede, J. B., Ele, P., Mveh-Abia, C. M., Toure, Y., Graefe, V. and Ma, S., “Intelligent mobile manipulator navigation using adaptive neuor-fuzzy systems,” Inf. Sci. 171 (4), 447–474 (2005).CrossRefGoogle Scholar
21.Najjaran, H. and Goldenberg, A., “Real-time motion planning of an autonomous mobile manipulator using fuzzy adaptive Kalman filter,” Robot. Auton. Syst. 55 (2), 96–106 (2007).CrossRefGoogle Scholar
22.Hammer, B., Koterba, S., Shi, J., Simmons, R. and Singh, S., “An autonomous mobile manipulator for assembly tasks,” Auton. Robots 28 (1), 131–149 (2010).CrossRefGoogle Scholar
23.Buss, M., Lee, K. K., Nitzsche, N., Peer, A., Stanczyk, B. and Unterhinninghofen, U., “Advanced telerobotics: Dual-Handed and mobile remote manipulation,” Adv. Telerobotics 31, 471–497 (2007).CrossRefGoogle Scholar
24.Anderson, D., Howard, T. M., Apfelbaum, D., Herman, H. and Kelly, A., “Coordinated control and range imaging for mobile manipulation,” Exp. Robot., 54, 547–556 (2009).CrossRefGoogle Scholar
25.Lizarralde, F. and Wen, J. T., “Quaternion-Based Coordinated Control of a Subsea Mobile Manipulator with only Position Measurements,” In: Proceedings of the 34th Conference on Decision & Control, New Orleans, LA (Dec. 1995) pp. 3996–4001.Google Scholar
26.Spellucci, P., DONLP2-INTV-DYN Users Guide (Technical University at Darmstadt, Darmstadt, Germany).Google Scholar
27.Willis, D., Nokleby, S.B. and Pop-Iliev, R., “Mechanical Design of the Jasper Mobile Manipulator,” Proceedings of the 2008 ASME International Design Engineering Technical Conferences, Brooklyn, USA (2008).Google Scholar