Skip to main content
SpringerLink
Log in

Stable Swarm Formation Control Using Onboard Sensor Information

  • Conference paper
Advances in Swarm Intelligence (ICSI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6146))

Included in the following conference series:

Abstract

In this paper, a stable leader-following formation control for multiple mobile robot systems with limited sensor information is studied. The proposed algorithm is to control a robot (follower) to follow another robot (leader), and easily extended to form any complex formation. The control algorithm requires information available from onboard sensors only, and utilizes estimation of leader’s acceleration in a simple form to reduce measurement of indirect information. There is also a rule to tune parameters of control in application.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Liu, B., Chu, T., Wang, L., Xie, G.: Controllability of a leader–follower dynamic network with switching topology. IEEE Trans. Autom. Control 53, 1009–1013 (2008)

    Article  MathSciNet  Google Scholar 

  2. Xu, W.B., Chen, X.B.: Artificial moment method for swarm robot formation control. Sci. China Ser. F-Inf. Sci. 51, 1521–1531 (2008)

    Article  MATH  Google Scholar 

  3. Reynolds, C.W.: Flocks, herds, and schools: A distributed behavioral model. Computer Graphics 21, 25–34 (1987)

    Article  Google Scholar 

  4. Lawton, J.R.T., Beard, R.W., Young, B.J.: A decentralized approach to formation maneuvers. IEEE Trans. Robot. Autom. 19(6), 933–941 (2003)

    Article  Google Scholar 

  5. Das, A.K., Fierro, R., Kumar, V., et al.: A vision-based formation control framework. IEEE Trans. Robot. Autom. 18, 813–825 (2002)

    Article  Google Scholar 

  6. Gustavi, T., Hu, X.: Observer-based leader-following formation control using onboard sensor information. IEEE Transactions on Robotics 24, 1457–1462 (2008)

    Article  Google Scholar 

  7. Wang, J., Wu, X., Xu, Z.: Potential-based obstacle avoidance in formation control. J. Control Theory Appl. 6, 311–316 (2008)

    Article  MathSciNet  Google Scholar 

  8. Barnes, L.E., Fields, M.A., Valavanis, K.P.: Swarm formation control utilizing elliptical surfaces and limiting functions. IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics 39, 1434–1445 (2009)

    Article  Google Scholar 

  9. Tanner, H.G., Jadbabaie, A., Pappas, G.J.: Flocking in teams of nonholonomic agents. Lect. Notes Contr. Inf., pp. 229–239. Springer, Berlin (2005)

    Google Scholar 

  10. Warburton, K., Lazarus, J.: Tendency-distance models of social cohesion in animal groups. Journal of Theoretical Biology 150, 473–488 (1991)

    Article  Google Scholar 

  11. Lewis, M.A., Tan, K.H.: High precision formation control of mobile robots using virtual structures autonomous. Autom Robot 4, 387–403 (1997)

    Article  Google Scholar 

  12. Egerstedt, M., Hu, X., Stotsky, A.: Control of mobile platforms using a virtual vehicle approach. IEEE Trans. Robot. Autom. 46, 1777–1782 (2001)

    MATH  MathSciNet  Google Scholar 

  13. Desai, J.P.: A graph theoretic approach for modeling mobile robot team formation. J. Robot Syst. 19, 511–525 (2002)

    Article  MATH  Google Scholar 

  14. Fierro, R., Das, A.K.: A modular architecture for formation control. In: Proceedings of the 3rd Int. Workshop on Robot Motion and Control, Poznan, pp. 285–290. IEEE Press, Los Alamitos (2002)

    Chapter  Google Scholar 

  15. Kang, W., Xi, N., Zhao, Y., Tan, J., Wang, Y.: Formation control of multiple autonomous vehicles- Theory and experimentation. Intell. Autom. Soft Comput. 10(2), 1–17 (2004)

    Google Scholar 

  16. Tanner, H.G., Pappas, G.J., Kumar, V.: Leader-to-formation stability. IEEE Trans. Robot. Autom. 20(3), 443–455 (2004)

    Article  Google Scholar 

  17. Gustavi, T., Hu, X., Karasalo, M.: Robust formation adaptation using on-board sensor information. In: 24th Chinese Control Conference, Guangzhou, pp. 1782–1788 (2005)

    Google Scholar 

  18. Khalil, H.: Nonlinear Systems, 2nd edn. Prentice Hall, New Jersey (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Yeungnam University, Gyeongsan, Korea

    Viet-Hong Tran & Suk-Gyu Lee

Authors
  1. Viet-Hong Tran
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Suk-Gyu Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Ying Tan

  2. Research and Postgraduate Office, Xi’an Jiaotong-Liverpool University, 215123, Suzhoum, China

    Yuhui Shi

  3. Department of Electrical and Computer Engineering, Engineering Drive 3, 4 Engineering Drive 3, National University of Singapore, 117576, Singapore

    Kay Chen Tan

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tran, VH., Lee, SG. (2010). Stable Swarm Formation Control Using Onboard Sensor Information. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13498-2_35

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-13498-2_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13497-5

  • Online ISBN: 978-3-642-13498-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation