Skip to main content

Swarm Robot Flocking: An Empirical Study

  • Conference paper
Intelligent Robotics and Applications (ICIRA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7102))

Included in the following conference series:

Abstract

Robots can be used in exploration or investigation of unknown terrains especially if the environment is dangerous. It is customary to employ a sophisticated robot for such task. However, this approach is vulnerable since a failure of the robot means, failure of the entire mission. An emerging approach in robotics research is to employ many simple robots that can collectively achieve a demanding task. Even the failure of some robots should not affect the overall mission. Maneuvering such large systems poses new challenges in controlling them. In our earlier work, a control strategy, namely triangular formation algorithm (TFA), was developed and tested using simulation tools. The TFA is a local interaction strategy which basically makes three neighboring robots to form a regular triangular lattice. Simulation results show that swarm behaviors such as aggregation, flocking and obstacle avoidance can be achieved successfully. Here, we are concerned with implementing the algorithm in practice with real robots. We have developed a swarm of five robots and tested the performance of the algorithm in practice. This paper presents our initial findings.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Bayindir, L., Şahin, E.: A Review of Studies in Swarm Robotics. Turk. J. Elec. Engin. 15(2), 115–147 (2007)

    Google Scholar 

  2. Şahin, E.: Swarm Robotics: From Sources of Inspiration to Domains of Application. In: Şahin, E., Spears, W.M. (eds.) Swarm Robotics 2004. LNCS, vol. 3342, pp. 10–20. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  3. Reynolds, C.W.: Flocks, Herds, and Schools: A Distributed Behavioral Model. Computer Graphics 21(4), 25–34 (1987)

    Article  Google Scholar 

  4. Vicsek, T., Czirok, A., Jacob, E.B., Cohen, I., Schochet, O.: Novel Type of Phase Transitions in a System of Self-Driven Particles. Physical Review Letters 75, 1226–1229 (1995)

    Article  MathSciNet  Google Scholar 

  5. Jadbadaie, A., Lin, J., Morse, A.S.: Coordination of Groups of Mobile Autonomous Agents Using Nearest Neighbor Rules. IEEE Transactions on Automatic Control 48(6), 988–1001 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  6. Yang, Y., Xiong, N., Chong, N.Y., Défago, X.: A Decentralized and Adaptive Flock-ing Algorithm for Autonomous Mobile Robots. In: the 3rd International Conference on Grid and Pervasive Computing Workshops, pp. 262–268. IEEE Press (2008)

    Google Scholar 

  7. Kim, D.H., Wang, H., Shin, S.: Decentralized Control of Autonomous Swarm Sys-tems Using Artificial Potential Function-Analytical Design Guidelines. J. Int. Robot Systems 45, 36–394 (2006)

    Google Scholar 

  8. Li, X., Ercan, M.F., Fung, Y.F.: A Triangular Formation Strategy for Collective Behaviors of Robot Swarm. In: Gervasi, O., Taniar, D., Murgante, B., Laganà, A., Mun, Y., Gavrilova, M.L. (eds.) ICCSA 2009. LNCS, vol. 5592, pp. 897–911. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Goren, A., Uyar, E., Baser, O., Dicle, Z.: Sensor Fusion Using Dempster-Shaffer The-ory of Evidence in Autonomous Robot Navigation. Automatic Control and Robotics 7(1), 133–144 (2008)

    Google Scholar 

  10. Jaafar, J., McKenzie, E.: Dempster-Shafer’s Approach for Autonomous Virtual Agent Navigation in Virtual Environments. Engineering and Tech. (62), 389–393 (2010)

    Google Scholar 

  11. Wu, H., Siegel, M., Stiefelhagen, R., Yang, J.: Sensor Fusion Using Dempster-Shafer Theory. In: IEEE Instrumentation and Measurement Technology Conference (2002)

    Google Scholar 

  12. Li, X., Ercan, M.F.: Sensor Fusion and Interpretation for Swarm of Land Robots. Submitted to IEEE Int. Symposium on System Integration-SII2011 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ercan, M.F., Li, X. (2011). Swarm Robot Flocking: An Empirical Study. In: Jeschke, S., Liu, H., Schilberg, D. (eds) Intelligent Robotics and Applications. ICIRA 2011. Lecture Notes in Computer Science(), vol 7102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25489-5_48

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-25489-5_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25488-8

  • Online ISBN: 978-3-642-25489-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics