Coordinated flight control of miniature fixed-wing UAV swarms: methods and experiments


In this paper, we present our recent advances in both theoretical methods and field experiments for the coordinated control of miniature fixed-wing unmanned aerial vehicle (UAV) swarms. We propose a multi-layered group-based architecture, which is modularized, mission-oriented, and can implement large-scale swarms. To accomplish the desired coordinated formation flight, we present a novel distributed coordinated-control scheme comprising a consensus-based circling rendezvous, a coordinated path-following control for the leader UAVs, and a leader-follower coordinated control for the follower UAVs. The current framework embeds a formation pattern reconfiguration technique. Moreover, we discuss two security solutions (inter-UAV collision avoidance and obstacle avoidance) in the swarm flight problem. The effectiveness of the proposed coordinated control methods was demonstrated in field experiments by deploying up to 21 fixed-wing UAVs.

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  1. 1

    Giulietti F, Pollini L, Innocenti M. Autonomous formation flight. IEEE Control Syst, 2000, 20: 34–44

    Article  Google Scholar 

  2. 2

    Gu Y, Seanor B, Campa G, et al. Design and flight testing evaluation of formation control laws. IEEE Trans Contr Syst Technol, 2006, 14: 1105–1112

    Article  Google Scholar 

  3. 3

    Yang Y, Polycarpou M M, Minai A A. Multi-UAV cooperative search using an opportunistic learning method. J Dyn Sys Meas Control, 2007, 129: 716

    Article  Google Scholar 

  4. 4

    Qu Y H, Zhang F, Wu X W, et al. Cooperative geometric localization for a ground target based on the relative distances by multiple UAVs. Sci China Inf Sci, 2019, 62: 010204

    Article  Google Scholar 

  5. 5

    Michael N, Fink J, Kumar V. Cooperative manipulation and transportation with aerial robots. Auton Robot, 2011, 30: 73–86

    Article  Google Scholar 

  6. 6

    Jin Y, Minai A A, Polycarpou M M. Cooperative real-time search and task allocation in uav teams. In: Proceedings of the 42nd IEEE Conference on Decision and Control. New York: IEEE, 2003. 7–12

    Google Scholar 

  7. 7

    Xargay E, Kaminer I, Pascoal A, et al. Time-critical cooperative path following of multiple unmanned aerial vehicles over time-varying networks. J Guidance Control Dyn, 2013, 36: 499–516

    Article  Google Scholar 

  8. 8

    Cichella V, Kaminer I, Dobrokhodov V, et al. Cooperative path following of multiple multirotors over time-varying networks. IEEE Trans Automat Sci Eng, 2015, 12: 945–957

    Article  Google Scholar 

  9. 9

    Ren W, Beard R W. Distributed Consensus in Multi-vehicle Cooperative Control. Berlin: Springer, 2008

    Google Scholar 

  10. 10

    Li Z, Duan Z. Cooperative Control of Multi-Agent Systems: A Consensus Region Approach. Boca Raton: CRC Press, 2014

    Google Scholar 

  11. 11

    Wang X, Zeng Z, Cong Y. Multi-agent distributed coordination control: developments and directions via graph viewpoint. Neurocomputing, 2016, 199: 204–218

    Article  Google Scholar 

  12. 12

    Liu J W, Huang J. Leader-following consensus of linear discrete-time multi-agent systems subject to jointly connected switching networks. Sci China Inf Sci, 2018, 61: 112208

    MathSciNet  Article  Google Scholar 

  13. 13

    Ma L F, Wang Z D, Han Q-L, et al. Consensus control of stochastic multi-agent systems: a survey. Sci China Inf Sci, 2017, 60: 120201

    MathSciNet  Article  Google Scholar 

  14. 14

    Zhou J L, Yang J Y, Li Z K. Simultaneous attack of a stationary target using multiple missiles: a consensus-based approach. Sci China Inf Sci, 2017, 60: 070205

    MathSciNet  Article  Google Scholar 

  15. 15

    Wang X, Yadav V, Balakrishnan S. Cooperative uavformation flying with obstacle/collision avoidance. IEEE Trans Contr Syst Technol, 2007, 15: 672–679

    Article  Google Scholar 

  16. 16

    Abdessameud A, Tayebi A. Formation control of vtolunmanned aerial vehicles with communication delays. Automatica, 2011, 47: 2383–2394

    MathSciNet  Article  Google Scholar 

  17. 17

    Liao F, Teo R, Wang J L, et al. Distributed formation and reconfiguration control of vtoluavs. IEEE Trans Contr Syst Technol, 2017, 25: 270–277

    Article  Google Scholar 

  18. 18

    Zou Y, Zhou Z, Dong X, et al. Distributed formation control for multiple vertical takeoff and landing uavs with switching topologies. IEEE/ASME Trans Mechatron, 2018, 23: 1750–1761

    Article  Google Scholar 

  19. 19

    Nigam N, Bieniawski S, Kroo I, et al. Control of multiple uavs for persistent surveillance: algorithm and flight test results. IEEE Trans Contr Syst Technol, 2012, 20: 1236–1251

    Article  Google Scholar 

  20. 20

    Kushleyev A, Mellinger D, Powers C, et al. Towards a swarm of agile micro quadrotors. Auton Robot, 2013, 35: 287–300

    Article  Google Scholar 

  21. 21

    Dong X, Zhou Y, Ren Z, et al. Time-varying formation control for unmanned aerial vehicles with switching interaction topologies. Control Eng Practice, 2016, 46: 26–36

    Article  Google Scholar 

  22. 22

    Dong X, Zhou Y, Ren Z, et al. Time-varying formation tracking for second-order multi-agent systems subjected to switching topologies with application to quadrotor formation flying. IEEE Trans Ind Electron, 2017, 64: 5014–5024

    Article  Google Scholar 

  23. 23

    Dydek Z T, Annaswamy A M, Lavretsky E. Adaptive configuration control of multiple uavs. Control Eng Practice, 2013, 21: 1043–1052

    Article  Google Scholar 

  24. 24

    Liu H, Dong X, Lewis F L, et al. Robust formation control for multiple quadrotors subject to nonlinear dynamics and disturbances. In: Proceedings of the 14th IEEE International Conference on Control and Automation. New York: IEEE, 2018. 58–62

    Google Scholar 

  25. 25

    Xargay E, Dobrokhodov V, Kaminer I, et al. Time-critical cooperative control of multiple autonomous vehicles: Robust distributed strategies for path-following control and time-coordination over dynamic communications networks. IEEE Control Syst, 2012, 32: 49–73

    MathSciNet  Article  Google Scholar 

  26. 26

    Bayraktar S, Fainekos G E, Pappas G J. Experimental cooperative control of fixed-wing unmanned aerial vehicles. In: Proceedings of the 43rd IEEE Conference on Decision and Control. New York: IEEE, 2004. 4292–4298

    Google Scholar 

  27. 27

    Reynolds C W. Flocks, herds and schools: a distributed behavioral model. SIGGRAPH Comput Graph, 1987, 21: 25–34

    Article  Google Scholar 

  28. 28

    Hauert S, Leven S, Varga M, et al. Reynolds flocking in reality with fixed-wing robots: communication range vs. maximum turning rate. In: Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. New York: IEEE, 2011. 5015–5020

    Google Scholar 

  29. 29

    Chung T H, Clement M R, Day M A, et al. Live-fly, large-scale field experimentation for large numbers of fixed-wing UAVs. In: Proceedings of 2016 IEEE International Conference on Robotics and Automation. New York: IEEE, 2016. 1255–1262

    Google Scholar 

  30. 30

    Lan Y, Yan G, Lin Z. Synthesis of distributed control of coordinated path following based on hybrid approach. IEEE Trans Automat Contr, 2011, 56: 1170–1175

    MathSciNet  Article  Google Scholar 

  31. 31

    Chen H, Cong Y R, Wang X K, et al. Coordinated path following control of fixed-wing unmanned aerial vehicles. 2019. ArXiv: 1906.05453

  32. 32

    Kothari M, Postlethwaite I. A probabilistically robust path planning algorithm for UAVs using rapidly-exploring random trees. J Intell Robot Syst, 2013, 71: 231–253

    Article  Google Scholar 

  33. 33

    Wu J C, Zhou R, Dong Z N, et al. Formation flight control method of multiple UAVs based on guidance route (in Chinese). J Beijing Univ Aeronaut Astronaut, 2016, 42: 1518–1525

    Google Scholar 

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This work was partly supported by National Natural Science Foundation of China (Grant No. 61801494), and Joint Fund of Ministry of Education of China for Equipment Pre-research and Beijing Nova Program (Grant No. 2018047). The authors express their deepest gratitude to the SWARM TEAM of the NUDT. Without their hard work, the flight experiments could not be done.

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Correspondence to Lincheng Shen.

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Wang, X., Shen, L., Liu, Z. et al. Coordinated flight control of miniature fixed-wing UAV swarms: methods and experiments. Sci. China Inf. Sci. 62, 212204 (2019).

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  • unmanned aerial vehicle
  • cooperative control
  • formation control
  • distributed control
  • multiagent system