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Dynamic model based formation control and obstacle avoidance of multi-robot systems

Published online by Cambridge University Press:  01 May 2008

Celso De La Cruz  and
Ricardo Carelli
Celso De La Cruz*
Affiliation:
Instituto de Automática, Universidad Nacional de San Juan, Av. San Martín Oeste 1109, J5400ARL, Argentina.
Ricardo Carelli
Affiliation:
Instituto de Automática, Universidad Nacional de San Juan, Av. San Martín Oeste 1109, J5400ARL, Argentina.
*
*Corresponding author. E-mail: [email protected]
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Summary

This work presents, first, a complete dynamic model of a unicycle-like mobile robot that takes part in a multi-robot formation. A linear parameterization of this model is performed in order to identify the model parameters. Then, the robot model is input-output feedback linearized. On a second stage, for the multi-robot system, a model is obtained by arranging into a single equation all the feedback linearized robot models. This multi-robot model is expressed in terms of formation states by applying a coordinate transformation. The inverse dynamics technique is then applied to design a formation control. The controller can be applied both to positioning and to tracking desired robot formations. The formation control can be centralized or decentralized and scalable to any number of robots. A strategy for rigid formation obstacle avoidance is also proposed. Experimental results validate the control system design.

Keywords

Formation controlDynamic modelNon-holonomic mobile robotsNonlinear systems
Type
Article
Information
Robotica , Volume 26 , Issue 3 , May 2008 , pp. 345 - 356
Copyright
Copyright © Cambridge University Press 2008

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References

1.Antonelli, G. and Chiaverini, S., “Kinematic Control of a Platoon of Autonomous Vehicles,” IEEE International Conference on Robotics and Automation, Taipei, Taiwan (September 2003) pp. 1464–1469.Google Scholar
2.Aström, K. J. and Wittenmark, B., Adaptive Control (Addison-Wesley, 1995).Google Scholar
3.Balch, T. and Arkin, R. C., “Behavior-Based Formation Control for Multirobot teams,” IEEE Transactions on Robotics and Automation, 14 (6) (December 1998) pp. 926–939.Google Scholar
4.Balch, T. and Hybinette, M., “Social Potentials for Scalable Multi-Robot Formations,” IEEE International Conference on Robotics and Automation, San Francisco (April 2000) pp. 73–80.Google Scholar
5.Belta, C. and Kumar, V., “Trajectory Design for Formations of Robots by Kinetic Energy Shaping,” IEEE International Conference on Robotics and Automation, Washington, DC (May 2002) pp. 2593–2598.Google Scholar
6.Bishop, B. E., “Dynamics-Based Control of Robotic Swarms,” IEEE International Conference on Robotics and Automation, Orlando, Florida (May 2006) pp. 2763–768.Google Scholar
7.Boyden, F. D. and Velinsky, S. A., “Dynamic Modeling of Wheeled Mobile Robots for High Load Applications,” IEEE International Conference on Robotics and Automation, 4, (1994), pp. 3071–3078.Google Scholar
8.Carelli, R., Nasisi, O.Roberti, F. and Tosetti, S., “Direct visual tracking control of remote cellular robots,” 13th. Int. Symposium on Measurement and Control in Robotics – Towards advanced robots: Design, sensors, control, Applications – ISMCR'03, Madrid (December 2003), pp. 11–12.Google Scholar
9.Das, A. K., Fierro, R., Kumar, V., Ostrowski, J. P., Spletzer, J. and Taylor, C. J., “A vision-Based Formation Control Framework,” IEEE Transactions on Robotics and Automation, 18 (5), (October 2002) pp. 813–825.CrossRefGoogle Scholar
10.Desai, J. P., Ostrowski, J. and Kumar, V., “Controlling Formations of Multiple Mobile robots,” In Proc. IEEE International Conference Robotics and Automation, Leuven, Belgium (May 1998) pp. 2864–2869.Google Scholar
11.Fierro, R., Das, A. K., Kumar, V., and Ostrowski, J. P., “Hibrid Control of Formations of Robots,” In Proc. IEEE International Conference Robotics and Automation, Seoul, Korea (May 2001) pp. 3672–3677.Google Scholar
12.Fredslund, J. and Mataric, M. J., “Robot Formations Using only Local Sensing and Control,” IEEE International Symposium on Computational Intelligence in Robotics and Automation, Banff, Alberta, Canada (July 2001) pp. 308–313.Google Scholar
13.Kelly, R., Carelli, R., Zannatha, J. M. Ibarra and Monroy, C., “Formation Tracking Control of a Group of Mobile Robots,” In Spanish. VI Congreso Mexicano de Robótica, COMRob, Torreón, Coahuila, Mexico (October 2004).Google Scholar
14.Lawton, J. R. T., Beard, R. W. and Young, B. J., “A decentralized Approach to Formation Maneuvers,” IEEE Transactions on Robotics and Automation, 19 (6), (December 2003) pp. 933–941.CrossRefGoogle Scholar
15.Mariottini, G. L., Morbidi, F., Prattichizzo, D., Pappas, G. J. and Daniilidis, K., “Leader-Follower Formations: Uncalibrated Vision-Based Localization and Control,” IEEE International Conference on Robotics and Automation, Roma (April 2007) pp. 2403–2408.Google Scholar
16.Monteiro, S., Vaz, M., and Bicho, E., “Attractor Dynamics Generates Robot Formations: From Theory to Implementation,” IEEE International Conference on Robotics and Automation, New Orleans, LA (April 2004) pp. 2582–2587.CrossRefGoogle Scholar
17.Mut, V., Nasisi, O., Carelli, R., and Kuchen, B., “Tracking Adaptive Impedance Robot Control with Visual Feedback”, IEEE International Conference on Robotics and Automation, Leuven, Belgium (May 1998) pp. 2002–2007.Google Scholar
18.Reyes, F. and Kelly, R., “On Parameter Identification of Robot Manipulator,” IEEE International Conference on Robotics and Automation, Albuquerque, New Mexico (April 1997) pp. 1910–1915.Google Scholar
19.Sciavicco, L. and Siciliano, B., Modelling and Control of Robot Manipulators (Springer, 2000).CrossRefGoogle Scholar
20.Secchi, H., Carelli, R., and Mut, V., “An Experience on Stable Control of Mobile Robots”, Latin American Applied Research, Buenos Aires, Argentina, 33 (4), (October 2003) pp. 379–386.Google Scholar
21.Slotine, J. -J. and Li, W., Applied Nonlinear Control (Prentice Hall Int., 1991).Google Scholar
22.Stilwell, D. J. and Bishop, B. E., “A Strategy for Controlling Autonomous Robot Platoons”, IEEE Conference on Decision and Control, Sydney, Australia (December 2000) pp. 3483–3488.Google Scholar
23.Tan, K. H. and Lewis, M. A., “Virtual structures for high-precision cooperative mobile robotic control,” International Conference on Intelligent Robots and Systems 1 (November 1996) pp. 132–139.Google Scholar
24.Vidyasagar, M., Nonlinear Systems Analysis (Prentice-Hall Int., New Jersey, 1993).Google Scholar
25.Yamaguchi, H., Arai, T. and Beni, G., “A distributed control scheme for multiple robotic vehicles to make group formations,” Robot. Auton. Sys. 36, 125–147 (2001).Google Scholar
26.Zhang, Y., Hong, D., Chung, J. H. and Velinsky, S. A., “Dynamic Model Based Robust Tracking Control of a Differentially Steered Wheeled Mobile Robot,” Proceedings of the American Control Conference, Philadelphia, Pennsylvania (June 1998) pp. 850–855.Google Scholar