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Optimization-based formation of autonomous mobile robots

Published online by Cambridge University Press:  05 August 2010

Huan Zhang  and
Pubudu N. Pathirana
Huan Zhang
Affiliation:
Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia E-mail: Hzhang5@unimelb.edu.au
Pubudu N. Pathirana*
Affiliation:
School of Engineering and Information Technology, Deakin University, Pigdons Road, Geelong, VIC 3217, Australia
*
*Corresponding author. E-mail: Pubudu.Pathirana@deakin.edu.au
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Summary

The formation of autonomous mobile robots to an arbitrary geometric pattern in a distributed fashion is a fundamental problem in formation control. This paper presents a new asynchronous, memoryless (oblivious) algorithm to the formation problem via distributed optimization techniques. The optimization minimizes an appropriately defined difference function between the current robot distribution and the target geometric pattern. The optimization processes are performed independently by individual robots in their local coordinate systems. A movement strategy derived from the results of the distributed optimizations guarantees that every movement makes the current robot configuration approaches the target geometric pattern until the final pattern is reached.

Keywords

Swarm roboticsMobile robotsMulti-robot systemsMotion planningNavigation
Type
Articles
Information
Robotica , Volume 29 , Issue 4 , July 2011 , pp. 515 - 525
Copyright
Copyright © Cambridge University Press 2010

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References

1.Ando, H., Oasa, Y., Suzuki, I. and Yamashita, M., “A distributed memoryless point convergence algorithm for mobile robots with limited visibility,” IEEE Trans. Robot. Autom. 15 (5), 818–828 (1999).CrossRefGoogle Scholar
2.Balch, T. and Arkin, R. C., “Behavior-based formation control for multirobot teams,” IEEE Trans. Robot. Autom. 14 (6), 926–939 (1998).CrossRefGoogle Scholar
3.Cieliebak, M., Flocchini, P., Prencipe, G. and Santoro, N., “Solving the Robots Gathering Problem,” In LNCS 2719 (2003) pp. 1181–1196.Google Scholar
4.Darbha, S. and Rajagopal, K. R., “Intelligent cruise control systems and traffic flow stability,” Transp. Res. Part C 7, 329–352 (1999).Google Scholar
5.Fax, J. A. and Murray, R. M., “Information flow and cooperative control of vehicle formations,” IEEE Trans. Autom. Control 49 (9), 1465–1476 (2004).CrossRefGoogle Scholar
6.Flocchini, P., Prencipe, G., Santoro, N. and Widmayer, P., “Hard Task for Weak Robots: The Role of Common Knowledge in Pattern Formation by Autonomous Mobile Robots,” ISAAC'99 (1999) LNCS, vol. 1741, pp. 93–102.Google Scholar
7.Gazi, V. and Passino, K. M., “Stability analysis of swarms,” IEEE Trans. Autom. Control. 48 (4), 692–697 (2003).CrossRefGoogle Scholar
8.Giulietti, F., Pollini, L. and Innocenti, M., “Autonomous formation flight,” IEEE Control Syst. Mag. 20 (6), 34–44 (2000).Google Scholar
9.Jadbaie, A., Lin, J. and Morse, A. S., “Coordination of groups of mobile autonomous agents using nearest neighbor rules,” IEEE Trans. Autom. Control 48 (6), 988–1001 (2003).CrossRefGoogle Scholar
10.Lin, Z., Francis, B. and Maggiore, M., “Necessary and sufficient graphical conditions of formation control of unicycles,” IEEE Trans. Autom. Control 50 (1), 121–127 (2005).Google Scholar
11.Liu, Y. and Passino, K. M., “Stable social foraging swarms in a noisy environment,” IEEE Trans. Autom. Control 49 (1), 30–44 (2004).CrossRefGoogle Scholar
12.Martinez, S., Cortes, J. and Bullo, F., “Motion coordination with distributed information,” IEEE Control Syst. Mag. 27 (4), 75–88 (Aug. 2007).Google Scholar
13.Savkin, A., “Coordinated collective motion of groups of autonomous mobile robots: Analysis of Vicsek's model,” IEEE Trans. Autom. Control 49 (6), 981–983 (2004).CrossRefGoogle Scholar
14.Sugihara, K. and Suzuki, I., “Distributed Motion Coordiantion of Multiple Mobile Robots,” Proceedings of the 5th IEEE International Symposium on Intelligent Control, Philadelphia, PA (1990) pp. 138–143.Google Scholar
15.Sugihara, K. and Suzuki, I., “Distributed algorithms for formation of geometric patterns with many mobile robots,” J. Robot. Syst. 13, 127–139 (1996).3.0.CO;2-U>CrossRefGoogle Scholar
16.Suzuki, I. and Yamashita, M., “Distributed anonymous mobile robots: Formation of geometric pattern,” SIAM J. Comput. 28 (4), 1347–1363 (1999).CrossRefGoogle Scholar
17.Warburton, K. and Lazarus, J., “Tendency-distance models of social cohesion in animal groups,” J. Theor. Bio. 150, 473–488 (1991).CrossRefGoogle ScholarPubMed