Skip to main content
Springer Nature Link
Log in

Formation Control of Multiple Rectangular Agents with Limited Communication Ranges

  • Conference paper
Advances in Visual Computing (ISVC 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8888))

Included in the following conference series:

Abstract

Formation control of multiple agents has attracted many robotic and control researchers recently because of its potential applications in various fields. This paper presents a novel approach to the formation control of multiple rectangular agents with limited communication ranges. The proposed distributed control algorithm is designed by utilizing an artificial potential function. The proposed control algorithm can guarantee fast formation performance and no collision among agents. As a result, the rectangular agents can move together and quickly form a pre-defined shape of formation such as straight line and circle, etc. Simulation results are conducted to demonstrate the effectiveness of the proposed algorithm.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

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.

Similar content being viewed by others

References

  1. Fierro, R., Das, A., Spletzer, J., Esposito, J., Kumar, V., Ostrowski, J.P., Pappas, G., Taylor, C.J., Hur, Y., Alur, R., Lee, I., Grudic, G., Southall, B.: A framework and architecture for multi-robot coordination. Inter. J. of Robotics Research 21(10-11), 977–995 (2002)

    Article  Google Scholar 

  2. Cruz, D., McClintock, J., Perteet, B., Orqueda, O., Cao, Y., Fierro, R.: Decentralized cooperative control - a multivehicle platform for research in networked embedded systems. IEEE on Control Systems 27(3), 58–78 (2007)

    Article  Google Scholar 

  3. Olfati-Saber, R.: Flocking for multi-agent dynamic systems: algorithms and theory. IEEE Trans. on Automatic Control 51(3), 401–420 (2006)

    Article  MathSciNet  Google Scholar 

  4. La, H.M., Sheng, W.: Dynamic targets tracking and observing in a mobile sensor network. J. of Robotics and Autonomous Sys. 60(7), 996–1009 (2012)

    Article  Google Scholar 

  5. La, H.M., Sheng, W.: Flocking control of a mobile sensor network to track and observe a moving target. In: IEEE Inter. Conf. on Robotics and Automation (ICRA), pp. 3129–3134 (2009)

    Google Scholar 

  6. Lynch, K.M., Yang, P., Freeman, R.A.: Decentralized environmental modeling by mobile sensor networks. IEEE Trans. on Robotics 24(3), 710–724 (2008)

    Article  Google Scholar 

  7. Cortes, J.: Distributed Kriged Kalman filter for spatial estimation. IEEE Trans. on Automatic Control 54(12), 2816–2827 (2009)

    Article  MathSciNet  Google Scholar 

  8. Lilienthal, A.J., Reggente, M., Trincavelli, M., Blanco, J.L., Gonzalez, J.: A statistical approach to gas distribution modeling with mobile robots-the kernel dm+v algorithm. In: IEEE Inter. Conf. on Intell. Robot Sys., pp. 570–576 (2009)

    Google Scholar 

  9. La, H.M., Sheng, W.: Distributed sensor fusion for scalar field mapping using mobile sensor networks. IEEE Trans. on Cybernetics 43(2), 766–778 (2013)

    Article  Google Scholar 

  10. La, H.M., Sheng, W., Chen, J.: Cooperative and active sensing in mobile sensor networks for scalar field mapping. IEEE Trans. on Systems, Man and Cybernetics, Part A: Systems (99), 1–12 (May 2014)

    Google Scholar 

  11. La, H.M., Lim, R.S., Du, J., Zhang, S., Yan, G., Sheng, W.: Development of a small-scale research platform for intelligent transportation systems. IEEE Trans. on Intelligent Transportation Systems 13(4), 1753–1762 (2012)

    Article  Google Scholar 

  12. Wang, Y., De Silva, C.W.: Sequential q -learning with kalman filtering for multirobot cooperative transportation. IEEE/ASME Trans. on Mechatronics 15(2), 261–268 (2010)

    Article  Google Scholar 

  13. Chen, J., Sun, D.: Coalition-based approach to task allocation of multiple robots with resource constraints. IEEE Trans. on Automation Science and Engineering 9(3), 516–528 (2012)

    Article  Google Scholar 

  14. Binetti, G., Naso, D., Turchiano, B.: Decentralized task allocation for surveillance systems with critical tasks. Robotics and Autonomous Systems 61(12), 1653–1664 (2013)

    Article  Google Scholar 

  15. Vig, L., Adams, J.A.: Multi-robot coalition formation. IEEE Trans. on Robotics 22(4), 637–649 (2006)

    Article  Google Scholar 

  16. Zhang, Y., Parker, L.E.: Iq-asymtre: Forming executable coalitions for tightly coupled multirobot tasks. IEEE Trans. on Robotics 29(2), 400–416 (2013)

    Article  Google Scholar 

  17. Korsah, G.A., Stentz, A., Dias, M.B.: A comprehensive taxonomy for multi-robot task allocation. The International Journal of Robotics Research 32(12), 1495–1512 (2013)

    Article  Google Scholar 

  18. La, H.M., Lim, R., Sheng, W.: Multi-robot cooperative learning for predator avoidance. IEEE Trans. on Control Systems Technology (99), 1–12 (2014)

    Google Scholar 

  19. La, H.M., Sheng, W.: Flocking control of multiple agents in noisy environments. In: IEEE Inter. Conf. on Robotics and Automation (ICRA), pp. 4964–4969 (2010)

    Google Scholar 

  20. Hu, J., Feng, G.: Distributed tracking control of leader–follower multi–agent systems under noisy measurement. Automatica 46(8), 1382–1387 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  21. Li, W., Spong, M.W.: Stability of general coupled inertial agents. IEEE Trans. on Automatic Control 55(6), 1411–1416 (2010)

    Article  MathSciNet  Google Scholar 

  22. Li, Z., Liu, X., Ren, W., Xie, L.: Distributed tracking control for linear multiagent systems with a leader of bounded unknown input. IEEE Transactions on Automatic Control 58(2), 518–523 (2013)

    Article  MathSciNet  Google Scholar 

  23. Li, W., Spong, M.W.: Analysis of flocking of cooperative multiple inertial agents via a geometric decomposition technique. IEEE Trans. on Systems, Man, and Cybernetics: Systems PP(99), 1 (2014)

    Google Scholar 

  24. La, H.M., Sheng, W.: Multi-agent motion control in cluttered and noisy environments. J. of Communications 8(1), 32–46 (2013)

    Article  Google Scholar 

  25. Do, K.D.: Flocking for multiple elliptical agents with limited communication ranges. IEEE Trans. on Robotics 27(5), 931–942 (2011)

    Article  Google Scholar 

  26. Do, K.D.: Formation control of multiple elliptical agents with limited sensing ranges. Automatica 48(7), 1330–1338 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  27. Dimarogonas, D.V., Kyriakopoulos, K.J.: Connectedness preserving distributed swarm aggregation for multiple kinematic robots. IEEE Transactions on 24(5), 1213–1223 (2008)

    Google Scholar 

  28. Zavlanos, M.M., Tanner, H.G., Jadbabaie, A., Pappas, G.J.: Hybrid control for connectivity preserving flocking. IEEE Trans. on Automatic Control 54(12), 2869–2875 (2009)

    Article  MathSciNet  Google Scholar 

  29. Kan, Z., Dani, A.P., Shea, J.M., Dixon, W.E.: Network connectivity preserving formation stabilization and obstacle avoidance via a decentralized controller. IEEE Trans. on Automatic Control 57(7), 1827–1832 (2012)

    Article  MathSciNet  Google Scholar 

  30. Do, K.D.: Bounded assignment formation control of second-order dynamic agents. IEEE/ASME Transactions on Mechatronics 19(2), 477–489 (2014)

    Article  Google Scholar 

  31. La, H.M., Sheng, W.: Adaptive flocking control for dynamic target tracking in a mobile sensor network. In: IEEE Inter. Conf. on Intell. Robots and Sys (IROS), pp. 4843–4848.

    Google Scholar 

  32. Cao, Y., Yu, W., Ren, W., Chen, G.: An overview of recent progress in the study of distributed multi-agent coordination. IEEE Transactions on Industrial Informatics 9(1), 427–438 (2013)

    Article  Google Scholar 

Download references

Authors
  1. Thang Nguyen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hung Manh La
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, University of Nevada at Reno, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, CA, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, NV, USA

    Darko Koracin

  5. The University of Texas at Dallas, 75080, Richardson, TX, USA

    Ryan McMahan

  6. NextGen Interactions, 27604, Raleigh, NC, USA

    Jason Jerald

  7. Indiana University, 46202, Indianapolis, IN, USA

    Hui Zhang

  8. Microsoft Research, 1 Microsoft Way, 98052, Redmond, WA, USA

    Steven M. Drucker

  9. University of Delaware, 19716-2712, Newark, DE, USA

    Chandra Kambhamettu

  10. Intel Corp., 95054, Sata Clara, CA, USA

    Maha El Choubassi

  11. Computer Graphics and Interactive Media Lab, Department of Computer Science, University of Houston, 77004, Houston, TX, USA

    Zhigang Deng

  12. NVIDIA, 34788, Leesburg, FL, USA

    Mark Carlson

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Nguyen, T., La, H.M. (2014). Formation Control of Multiple Rectangular Agents with Limited Communication Ranges. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_88

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-14364-4_88

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14363-7

  • Online ISBN: 978-3-319-14364-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics