Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-10T16:51:55.174Z Has data issue: false hasContentIssue false

Trajectory Tracking and Stability Analysis for Mobile Manipulators Based on Decentralized Control

Published online by Cambridge University Press:  06 March 2019

Raouf Fareh*
Affiliation:
Department of Electrical and Computer Eng., University of Sharjah, P.O.Box 27272, Sharjah, UAE
Mohamad R. Saad
Affiliation:
School of Engineering, Université du Québec en Abitibi-Témiscamingue, 445, boul. de l’Université, Rouyn-Noranda (Québec), J9X 5E4, Canada E-mail: mohamad.saad@uqat.ca
Maarouf Saad
Affiliation:
Electrical Engineering Department, Université du Québec, École de technologie supérieure, 1100, rue Notre-Dame ouest, Montréal (Québec), H3C 1K3, Canada E-mails: maarouf.saad@etsmtl.ca, abdelkrim.brahmi.1@ens.etsmtl.ca
Abdelkrim Brahmi
Affiliation:
Electrical Engineering Department, Université du Québec, École de technologie supérieure, 1100, rue Notre-Dame ouest, Montréal (Québec), H3C 1K3, Canada E-mails: maarouf.saad@etsmtl.ca, abdelkrim.brahmi.1@ens.etsmtl.ca
Maamar Bettayeb
Affiliation:
Department of Electrical and Computer Eng., University of Sharjah, P.O.Box 27272, Sharjah, UAE Department of Electrical and Computer Engineering, University of Sharjah, P.O.Box 27272, Sharjah, United Arab Emirates and CEIES, King Abdulaziz University, Jeddah, KSA E-mail: maamar@sharjah.ac.ae
*
*Corresponding author. E-mail: rfareh@sharjah.ac.ae

Summary

Trajectory tracking of a mobile manipulator in the Cartesian space based on decentralized control is considered in this paper. The dynamic model is first rearranged to take the form of two interconnected subsystems with constraint flow, namely, a nonholonomic mobile platform subsystem and a holonomic manipulator subsystem. Secondly, using the inverse kinematics, the workspace desired trajectory of the mobile manipulator is transformed to the manipulator joint space as well as the platform desired trajectory. The kinematic control is developed from the desired trajectory of the platform. Then, the desired velocity is derived using the kinematic controller of the mobile platform, after which the velocity is used to obtain the control law of the mobile platform subsystem. Thirdly, the control law of the manipulator subsystem is developed based on the desired and real values of the manipulator, as well as the desired velocity. According to the Lyapunov stability theory, the proposed decentralized control strategy guarantees the global stability of the closed-loop system, and the tracking errors are bounded. Experimental results obtained on a 3-DOF manipulator mounted on a mobile platform are given to demonstrate the feasibility and effectiveness of the proposed approach. This is confirmed by a comparison with the computed torque approach.

Type
Articles
Copyright
© Cambridge University Press 2019 

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

Galicki, M., “An adaptive non-linear constraint control of mobile manipulators,” Mech. Mach. Theory 88, 6385 (2015).CrossRefGoogle Scholar
Andaluz, V. H., Roberti, F., Salinas, L., Toibero, J.M. and Carelli, R., “Passivity-based visual feedback control with dynamic compensation of mobile manipulators: stability and L2-gain performance analysis,” Robot. Auton. Syst. 66, 6474 (2015).CrossRefGoogle Scholar
Jae Young, L. and Moon, S. M., “A simple active damping control for compliant base manipulators,” IEEE/ASME Trans. Mechatron. 6(3), 305310 (2001).Google Scholar
Yamamoto, Y. and Yun, X., “Coordinating Locomotion and Manipulation of a Mobile Manipulator,” Proceedings of the 31st IEEE Conference on Decision and Control, 1992 (1992) pp. 26432648: IEEE.Google Scholar
Papadopoulos, E. and Poulakakis, J., “Planning and Model-Based Control for Mobile Manipulators,” Proceedings of the 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2000. (IROS 2000), IEEE (2000), 3, pp. 18101815.Google Scholar
Lee, C.-Y., Jeong, I.-K., Lee, I.-H. and Lee, J.-J., “Motion Control of Mobile Manipulator Based on Neural Networks and Error Compensation,” Proceedings of the ICRA’04. 2004 IEEE International Conference on Robotics and Automation, 2004, IEEE (2004), 5, pp. 46274632.Google Scholar
Chin Pei, T., Miller, P. T., Krovi, V. N., Ji-Chul, R. and Agrawal, S. K., “Differential-flatness-based planning and control of a wheeled mobile manipulator-theory and experiment,” IEEE/ASME Trans. Mechatron. 16(4), 768773, (2011).Google Scholar
Minami, M., Kotsuru, T. and Asakura, T., “Tracking Control of Non-Holonomic Mobile Manipulators,” In: 4th Asia-Pacific Conference on Control and Measurement, Guilin, China (2000) pp. 361366.Google Scholar
Bourbonnais, F., Bigras, P. and Bonev, I. A., “Minimum-time trajectory planning and control of a pick-andplace five-bar parallel robot,” IEEE/ASME Trans. Mechatron. 20(2), 740749 (2015).CrossRefGoogle Scholar
Lins Barreto, J. C., Scolari Conceicao, S. A. G., Dorea, C. E. T., Martinez, L. and de Pieri, E. R., “Design and implementation of model-predictive control with friction compensation on an omnidirectional mobile robot,” IEEE/ASME Trans. Mechatron. 19(2), 467476 (2014).CrossRefGoogle Scholar
Yamamoto, Y. and Yun, X., “Effect of the dynamic interaction on coordinated control of mobile manipulators,” IEEE Trans. Robot. Automat. 12(5), 816824 (1996).CrossRefGoogle Scholar
Yamamoto, Y. and Yun, X., “Modeling and Compensation of the Dynamic Interaction of a Mobile Manipulator,” Proceedings of the 1994 IEEE International Conference on Robotics and Automation, 1994, IEEE (1994) pp. 21872192.Google Scholar
Liu, K. and Lewis, F. L., “Decentralized Continuous Robust Controller for Mobile Robots,” In: 1990 IEEE International Conference on Robotics and Automation, 13–18 May 1990, IEEE Comput. Soc. Press: Los Alamitos, CA, USA (1990) pp. 18221827.Google Scholar
Inoue, F., Murakami, T. and Ohnishi, K., “A motion control of mobile manipulator with external force,” IEEE/ASME Trans. Mechatron. 6(2), 137142 (2001).CrossRefGoogle Scholar
Liu, K. and Lewis, F. L., “Decentralized Continuous Robust Controller for Mobile Robots,” Proceedings of the 1990 IEEE International Conference on Robotics and Automation, 1990, IEEE (1990) pp. 18221827.Google Scholar
Chung, J. H., Velinsky, S. A. and Hess, R. A., “Interaction control of a redundant mobile manipulator,” Int. J. Robot. Res. 17(12), 13021309 (1998).CrossRefGoogle Scholar
White, G. D., Bhatt, R. M., Tang, C. P. and Krovi, V. N., “Experimental evaluation of dynamic redundancy resolution in a nonholonomic wheeled mobile manipulator,” IEEE/ASME Trans. Mechatron. 14(3), 349357, (2009).CrossRefGoogle Scholar
Lin, S. and Goldenberg, A. A., “Neural-network control of mobile manipulators,” Neur. Netw. IEEE Trans. 12(5), 11211133, (2001).Google ScholarPubMed
Wang, H. and Wang, Q., “Robust and adaptive fuzzy control for mobile manipulator,” Cont. Decis. 25(3), 461465 (2010).Google Scholar
Andaluz, V., Roberti, F., Toibero, J. M. and Carelli, R., “Adaptive unified motion control of mobile manipulators,” Cont. Eng. Pract. 20(12), 13371352 (2012).CrossRefGoogle Scholar
Shojaei, K. and Shahri, A. M., “Output feedback tracking control of uncertain non-holonomic wheeled mobile robots: A dynamic surface control approach,” Cont. Theory Appl. IET 6(2), 216228 (2012).CrossRefGoogle Scholar
Ahmad, S., Zhang, H. and Liu, G., “Multiple working mode control of door-opening with a mobile modular and reconfigurable robot,” IEEE/ASME Trans. Mechatron. 18(3), 833844 (2013).CrossRefGoogle Scholar
Dietrich, A., Bussmann, K., Petit, F., Kotyczka, P., Ott, C., Lohmann, B. and Albu-Schäffer, A., “Whole-body impedance control of wheeled mobile manipulators,” Auton. Robots 40(3), 505517 (2016).CrossRefGoogle Scholar
Mazur, A. and Cholewiński, M., “Virtual force concept in steering mobile manipulators with skid-steering platform moving in unknown environment,” J. Intell. Robot. Syst. 77(3–4), 433443 (2015).CrossRefGoogle Scholar
Kraus, T., Ferreau, H. J., Kayacan, E., Ramon, H., De Baerdemaeker, J., Diehl, M. and Saeys, W., “Moving horizon estimation and nonlinear model predictive control for autonomous agricultural vehicles,” Comput. Electron. Agric. 98, 2533 (2013).CrossRefGoogle Scholar
Li, Z. and Ge, S. S., Fundamentals in Modeling and Control of Mobile Manipulators (CRC Press, Boca Raton, USA, 2013).Google Scholar
Kanayama, Y., Kimura, Y., Miyazaki, F. and Noguchi, T., “A Stable Tracking Control Method for an Autonomous Mobile Robot,” Proceedings of the 1990 IEEE International Conference on Robotics and Automation, 1990, IEEE (1990) pp. 384389.Google Scholar
Hou, M., Duan, G. and Guo, M., “New versions of Barbalat’s lemma with applications,” J. Cont. Theory Appl. 8(4), 545547 (2010).CrossRefGoogle Scholar
Samson, C. and Ait-Abderrahim, K., “Feedback Control of a Nonholonomic Wheeled Cart in Cartesian Space,” Proceedings of the 1991 IEEE International Conference on Robotics and Automation, 1991, IEEE (1991) pp. 11361141.Google Scholar
Mehrjerdi, H., Ghommam, J. and Saad, M., “Nonlinear coordination control for a group of mobile robots using a virtual structure,” Mechatronics 21(7), 11471155, (2011).CrossRefGoogle Scholar
Hassan, K., “Khalil, Nonlinear Systems,” (Prentice-Hall, Inc., New Jersey, 1996).Google Scholar
Watanabe, K., Sato, K., Izumi, K. and Kunitake, Y., “Analysis and control for an omnidirectional mobile manipulator,” J. Intell. Robot. Syst. 27(1–2), 320 (2000).CrossRefGoogle Scholar
Craig, J. J., Introduction to Robotics: Mechanics and Control (Pearson, Prentice Hall Upper Saddle River, NJ, USA, 2005).Google Scholar