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Mathematical Problems in Engineering
Volume 2013, Article ID 368369, 9 pages
http://dx.doi.org/10.1155/2013/368369
Research Article

Modeling and Flocking Consensus Analysis for Large-Scale UAV Swarms

School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China

Received 31 July 2013; Accepted 7 October 2013

Academic Editor: J. A. Tenreiro Machado

Copyright © 2013 Li Bing et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. B. Duan, Q. N. Luo, and G. J. Ma, “Hybrid particle swarm optimization and genetic algorithm for multi-UAV formation reconfiguration,” IEEE Computational Intelligence Magazine, vol. 8, pp. 16–27, 2013. View at Google Scholar
  2. W. Yi, M. B. Blake, and R. G. Madey, “An operation-time simulation framework for UAV swarm configuration and mission planning,” Procedia Computer Science, vol. 18, pp. 1949–1958, 2013. View at Publisher · View at Google Scholar
  3. Y. Tang, H. J. Gao, J. Kurths, and J.-A. Fang, “Evolutionary pinning control and its application in UAV coordination,” IEEE Transactions on Industrial Informatics, vol. 8, no. 4, pp. 828–838, 2012. View at Publisher · View at Google Scholar
  4. G. B. Lamont, J. N. Slear, and K. Melendez, “UAV swarm mission planning and routing using multi-objective evolutionary algorithms,” in Proceedings of the 1st IEEE Symposium of Computational Intelligence in Multicriteria Decision Making (MCDM '07), pp. 10–20, April 2007. View at Publisher · View at Google Scholar · View at Scopus
  5. E. Besada-Portas, L. de la Torre, J. M. de la Cruz, and B. de Andrés-Toro, “Evolutionary trajectory planner for multiple UAVs in realistic scenarios,” IEEE Transactions on Robotics, vol. 26, no. 4, pp. 619–634, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. S. Kanchanavally, R. Ordonez, and C. J. Schumacher, “Path planning in three dimensional environment using feedback linearization,” in Proceedings of the American Control Conference (ACC '06), pp. 3545–3550, Mineapolis, Minn, USA, June 2006. View at Scopus
  7. M. Shanmugavel, A. Tsourdos, R. Zbikowski, and B. A. White, “3D path planning for multiple UAVs using pythagorean hodograph curves,” in Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, pp. 1576–1589, Hilton Head, SC, USA, August 2007. View at Scopus
  8. I. Hasircioglu, H. R. Topcuoglu, and M. Ermis, “3-D path planning for the navigation of unmanned aerial vehicles by using evolutionary algorithms,” in Proceedings of the 10th Annual Genetic and Evolutionary Computation Conference (GECCO '08), pp. 1499–1506, July 2008. View at Scopus
  9. P. Vincent and I. Rubin, “A framework and analysis for cooperative search using UAV swarms,” in Proceedings of the ACM Symposium on Applied Computing, pp. 79–86, 2004.
  10. G. Varela, P. Caamamño, F. Orjales, Á. Deibe, F. López-Peña, and R. J. Duro, “Swarm intelligence based approach for real time UAV team coordination in search operations,” in Proceedings of the 3rd World Congress on Nature and Biologically Inspired Computing (NaBIC '11), pp. 365–370, October 2011. View at Publisher · View at Google Scholar · View at Scopus
  11. Y. l. Yang, Cooperative search by uninhabited air vehicles in dynamic environment [Ph.D. thesis], University of Cincinnati, Cincinnati, Ohio, USA, 2005.
  12. P. Dasgupta, “A multiagent swarming system for distributed automatic target recognition using unmanned aerial vehicles,” IEEE Transactions on Systems, Man, and Cybernetics A, vol. 38, no. 3, pp. 549–563, 2008. View at Publisher · View at Google Scholar · View at Scopus
  13. M. Yunhong, J. Zhe, and Z. Deyun, “A faster pruning optimization algorithm for task assignment,” Journal of Northwestern Polytechnical University, vol. 31, pp. 40–43, 2013. View at Google Scholar
  14. B. Di, R. Zhou, and Q.-X. Ding, “Distributed coordinated heterogeneous task allocation for unmanned aerial vehicles,” Control and Decision, vol. 28, pp. 274–278, 2013. View at Google Scholar
  15. W. You, Sh. Wang, and J. Tao, “Multi-UAV dynamic task assignment by ISODATA restrained clustering,” Electronics Optics & Control, vol. 17, pp. 22–26, 2010. View at Google Scholar
  16. D. Dionne and C. A. Rabbath, “Multi-UAV decentralized task allocation with intermittent communications: the DTC algorithm,” in Proceedings of the American Control Conference (ACC '07), pp. 5406–5411, July 2007. View at Publisher · View at Google Scholar · View at Scopus
  17. P. Dasgupta and M. Hoeing, “Dynamic pricing algorithms for task allocation in multi-agent swarms,” in Massively Multi-Agent Technology, N. Jamali, P. Scerri, and T. Sugawara, Eds., vol. 5043 of Lecture Notes in Computer Science, pp. 64–79, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. P. Gaudiano, B. Shargel, and E. Bonabeau, Swarm Intelligence: A New C2 Paradigm with an Application to Control Swarms of UAVs, Icosystem, Cambridge, Mass, USA, 2003.
  19. J. Finke, K. M. Passino, S. Ganapathy, and A. Sparks, “Modeling and analysis of cooperative control systems for uninhabited autonomous vehicles,” in Cooperative Control, V. Kumar, N. Leonard, and A. S. Morse, Eds., vol. 309 of Lecture Notes in Control and Information Science, pp. 79–102, Springer, New York, NY, USA, 2005. View at Publisher · View at Google Scholar · View at MathSciNet
  20. T. McLain, R. Beard, and J. Kelsey, “Experimental demonstration of multiple robot cooperative target intercept,” in Proceedings of the AIAA Guidance, Navigation, and Control Conference, AIAA-2002-4678, 2002.
  21. A. Moitra, R. Szczerba, V. Didomizio, L. Hoebel, R. Mattheyses, and B. Yamrom, “A novel approach for the coordination of multi-vehicle teams,” in Proceedings of the AIAA Guidance, Navigation, and Control Conference, pp. 608–618, Monterey, Calif, USA, 2001.
  22. P. Vincent and I. Rubin, “A framework and analysis for cooperative search using UAV swarms,” in Proceedings of the ACM Applied Computing, pp. 79–86, Nicosia, Cyprus, 2004.
  23. H. Hexmoor, B. McLaughlan, and M. Baker, “Swarm control in unmanned aerial vehicles,” in Proceedings of the International Conference on Artificial Intelligence (ICAI '05), pp. 911–917, June 2005. View at Scopus
  24. R. Garcia and L. Barnes, “Multi-UAV simulator utilizing x-plane,” Journal of Intelligent and Robotic Systems, vol. 57, no. 1–4, pp. 393–406, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  25. M. A. Russell, G. B. Lamont, and K. Melendez, “On using SPEEDES as a platform for a parallel swarm simulation,” in Proceedings of the Winter Simulation Conference, pp. 1129–1137, December 2005. View at Publisher · View at Google Scholar · View at Scopus
  26. S. Luke, C. Cioffi-Revilla, L. Panait, K. Sullivan, and G. Balan, “MASON: a multiagent simulation environment,” Simulation, vol. 81, no. 7, pp. 517–527, 2005. View at Publisher · View at Google Scholar · View at Scopus
  27. S. J. Rasmussen, J. W. Mitchell, P. R. Chandler, C. J. Schumacher, and A. L. Smith, “Introduction to the Multi-UAV2 simulation and its application to cooperative control research,” in Proceedings of the American Control Conference (ACC '05), pp. 4490–4501, June 2005. View at Scopus
  28. T. McLain, R. Beard, and J. Kelsey, “Experimental demonstration of multiple robot cooperative target intercept,” in Proceedings of the AIAA Guidance, Navigation, and Control Conference, AIAA-2002-4678, Monterey, Calif, USA, 2002.
  29. H. G. Tanner, A. Jadbabaie, and G. J. Pappas, “Stable flocking of mobile agents, part I: fixed topology,” in Proceedings of the 42nd IEEE Conference on Decision and Control, pp. 2010–2015, December 2003. View at Scopus
  30. H. G. Tanner, A. Jadbabaie, and G. J. Pappas, “Stable flocking of mobile agents part II: dynamic topology,” in Proceedings of the 42nd IEEE Conference on Decision and Control, pp. 2016–2021, December 2003. View at Scopus
  31. M. J. Mataric, Interaction and intelligent behavior [Ph.D. thesis], Massachusetts Institute of Technology, Cambridge, Mass, USA, 1994.
  32. I. Kelly and D. Keating, “Flocking by the fusion of sonar and active infrared sensors on physical autonomous robots,” in Proceedings of the Conference on Mechatronics and Machine Vision in Practice, pp. 14–17, 1996.
  33. A. T. Hayes and P. Dormiani-Tabatabaei, “Self-organized flocking with agent failure: off-line optimization and demonstration with real robots,” in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3900–3905, May 2002. View at Scopus
  34. O. Holland, J. Woods, R. de Nardi, and A. Clark, “Beyond swarm intelligence: the ultraswarm,” in Proceedings of the IEEE Swarm Intelligence Symposium (SIS '05), pp. 217–224, June 2005. View at Publisher · View at Google Scholar · View at Scopus
  35. E. Ferrante, A. E. Turgut, N. Mathews, M. Birattari, and M. Dorigo, “Flocking in stationary and non-stationary environments: a novel communication strategy for heading alignment,” in Parallel Problem Solving from Nature—PPSN XI, R. Schaefer, C. Cotta, J. Kolodziej, and G. Rudolph, Eds., vol. 6239 of Lecture Notes in Computer Science, pp. 331–340, 2010. View at Publisher · View at Google Scholar · View at Scopus
  36. A. Stranieri, E. Ferrante, A. E. Turgut et al., “Self-organized flocking with a heterogeneous mobile robot swarm,” Tech. Rep., 2011. View at Google Scholar
  37. B. Li, “Stochastic process model of the multi-UAVs collaborative system based on state transition,” in Proceedings of Conference on Modeling, Identification and Control, pp. 757–761, 2012.
  38. Z. X. Chen, Partial Differential Equations, Science Press, Beijing, China, 2002.
  39. L. Guo, H. Xu, C. Gao, and G. Zhu, “Stability analysis of a new kind series system,” IMA Journal of Applied Mathematics, vol. 75, no. 3, pp. 439–460, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet · View at Scopus
  40. D. p. Gaver, “Time to failure and availability of paralleled system with repair,” IEEE Transactions on Reliability, vol. 12, pp. 30–38, 1963. View at Google Scholar
  41. Q. J. Fan, Key techniques research of cooperative formation biomimetic flight control for multi-UAV [Ph.D. thesis], Nanjing University of Aeronautics and Astronautics, Nanjing, China, 2008.
  42. C. Yancai, Research on distributed cooperative control for swarm UAVs [Ph.D. thesis], Nanjing University of Aeronautics and Astronautics, Nanjing, China, 2011.