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Minimum control effort trajectory planning and tracking of the CEDRA brachiation robot

Published online by Cambridge University Press:  14 May 2013

Ali Meghdari*
Affiliation:
Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
Seyyed Mohammad H. Lavasani
Affiliation:
Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
Mohsen Norouzi
Affiliation:
Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
Mir Saman Rahimi Mousavi
Affiliation:
Center of Excellence in Design, Robotics and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran
*
*Corresponding author. E-mail: Meghdari@sharif.edu

Summary

The control of a brachiation robot has been the primary objective of this study. A brachiating robot is a type of a mobile arm that is capable of moving from branch to branch similar to a long-armed ape. In this paper, to minimize the actuator work, Pontryagin's minimum principle was used to obtain the optimal trajectories for two different problems. The first problem considers “brachiation between fixed branches with different distance and height,” whereas the second problem deals with the “brachiating and catching of a moving target branch”. Theoretical results show that the control effort in the proposed method is reduced by 25% in comparison with the “target dynamics” method which was proposed by Nakanishi et al. (1998)16 for the same type of robot. As a result, the obtained optimal trajectory also minimizes the brachiation time. Two kinds of controllers, namely the proportional-derivative (PD) and the adaptive robust (AR), were investigated for tracking the proposed trajectories. Then, the previous method on a set-point controller for acrobat robots is improved to represent a new AR controller which allows the system to track the desired trajectory. This new controller has the capability to be used in systems which have uncertainties in the kinematic and dynamic parameters. Finally, theoretical results are presented and validated with experimental observations with a PD controller due to the no chattering phenomenon and small computational efforts.

Type
Articles
Information
Robotica , Volume 31 , Issue 7 , October 2013 , pp. 1119 - 1129
Copyright
Copyright © Cambridge University Press 2013 

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References

Nakanishi, J., Fukuda, T. and Koditschek, D. E., “Preliminary Studies of a Second Generation Brachiation Robot Controller,” Proceedings of the IEEE International Conference on Robotics and Automation, Albuquerque, NM, USA (1997) pp. 20502056.CrossRefGoogle Scholar
Fukuda, T., Hosokai, H. and Kondo, Y., “Brachiation Type of Mobile Robot,” Proceedings of the Fifth International Conference on Advanced Robotics, Robots in Unstructured Environments, vol. 2, Pisa, Italy, (1991) pp. 915920.Google Scholar
De Oliveira, V. M. and Lages, W. F., “MPC Applied to Motion Control of an Underactuated Brachiation Robot,” Proceedings of the IEEE Symposium on Emerging Technologies and Factory Automation, ETFA, Hamburg, Germany (2006) pp. 985988.Google Scholar
De Oliveira, V. M. and Lages, W. F., “Control of a brachiating robot for inspection of aerial power lines,” Proceedings of the 1st International Conference on Applied Robotics for the Power Industry (CARPI), Montreal, QC (2010) pp. 16.Google Scholar
Lee, D., Burg, T. C., Dawson, D. M., Shu, D., Xian, B. and Tatlicioglu, E., “Robust tracking control of an underactuated quadrotor aerial-robot based on a parametric uncertain model,” Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, San Antonio, TX (2009) pp. 31873192.Google Scholar
Azinheira, J. R., Moutinho, A. and De Paiva, E. C., “A backstepping controller for path-tracking of an underactuated autonomous airship,” Int. J. Robust Nonlinear Control, 19, 418441 (2009).CrossRefGoogle Scholar
Chen, W., Zhao, L., Zhao, X. and Yu, Y., “Control of the underactuated flexible manipulator in the operational space,” Proceedings of the International Conference on Intelligent Human-Machine Systems and Cybernetics, Hangzhou, Zhejiang (2009) pp. 470473.Google Scholar
Spong, M. W., “Swing up control problem for the acrobot,” IEEE Control Syst. Mag. 15, 4955 (1995).CrossRefGoogle Scholar
Park, M. S. and Chwa, D., “Swing-up and stabilization control of inverted-pendulum systems via coupled sliding-mode control method,” IEEE Trans. Ind. Electron. 56, 35413555 (2009).CrossRefGoogle Scholar
Fukuda, T., Saito, F. and Arai, F., “Study on the Brachiation Type of Mobile Robot (Heuristic creation of driving input and control using CMAC),” Proceedings of the IEEE/RSJ International Workshop on Intelligent Robot and Systems ‘91, Osaka, Japan (1991) pp. 478483.CrossRefGoogle Scholar
Saito, F., Fukuda, T. and Arai, F., “Swing and locomotion control for a two-link Brachiation robot,” IEEE Control Syst. Mag. 14, 511 (1994).CrossRefGoogle Scholar
Saito, F., Fukuda, T., Arai, F. and Kosuge, K., “Heuristic generation of driving input and control of brachiation robot,” JSME Int. J. 37, 147154 (1994).Google Scholar
Gomes, M. W. and Ruina, A. L., “A five-link 2D brachiating ape model with life-like zero-energy-cost motions,” J. Theor. Biol. 237, 265278 (2005).CrossRefGoogle ScholarPubMed
Nishimura, H. and Funaki, K., “Motion control of brachiation robot by using final-state control for parameter-varying systems,” Proceedings of the 35th IEEE Conference on Decision and Control, Kobe, Japan (1996) pp. 23553592.Google Scholar
Nishimura, H. and Funaki, K., “Motion control of three-link brachiation robot by using final-state control with error learning,” IEEE/ASME Trans. Mechatronics 3, 120128 (1998).CrossRefGoogle Scholar
Nakanishi, J., Fukuda, T. and Koditschek, D. E., “Experimental Implementation of a ‘Target Dynamics’ Controller on a Two-Link Brachiating Robot,” Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium (1998) pp. 787792.Google Scholar
Nakanishi, J., Fukuda, T. and Koditschek, D. E., “Hybrid Swing up Controller for a Two-Link Brachiating Robot,” Proceedings of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics (1999) pp. 549–554.Google Scholar
Nakanishi, J., Fukuda, T. and Koditschek, D. E., “A brachiating robot controller,” IEEE Trans. Robot. Autom. 16, 109123 (2000).CrossRefGoogle Scholar
Nakanishi, J. and Fukuda, T., “Preliminary analytical approach to a brachiation robot controller,” Technical report: CGR 96–08 / CSE TR 305-96, The University. of Michigan, EECS Department (1996).Google Scholar
Nakanishi, J., Fukuda, T. and Koditschek, D. E., “Brachiation on a ladder with irregular intervals,” Adv. Robot. 16, 147160 (2002).CrossRefGoogle Scholar
De Oliveira, V. M. and Lages, W. F., “Linear Predictive Control of a Brachiation Robot,” Proceedings of the Canadian Conference on Electrical and Computer Engineering, Ottawa, ON (2007) pp. 15181521.Google Scholar
Baruh, H., Analytical Dynamics (McGraw-Hill, New York 1998).Google Scholar
Kirk, D. E., Optimal Control Theory: An Introduction (Prentice-Hall, Englewood Cliffs, NJ 1970).Google Scholar
Stoer, J. and Bulirsch, R., Introduction to Numerical Analysis, 2nd ed. (Springer-Verlag, New York, 1980).CrossRefGoogle Scholar
Su, C. Y. and Stepanenko, Y., “Adaptive variable structure set-point control of underactuated robots,” IEEE Trans. Autom. Control 44, 20902093 (1999).Google Scholar
Leavitt, J., Sideris, A. and Bobrow, J. E., “High bandwidth tilt measurement using low cost sensors,” Mechatronics, IEEE/ASME Trans. vol. 11, pp. 320327, (2006).CrossRefGoogle Scholar
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