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Reconfiguration Between Longitudinal and Circular Formations for Multi-UAV Systems by Using Segments

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Abstract

In typical monitoring applications, such as fires or deforestation, the agents of the unmanned aircraft squadron must follow a circular motion. However, for other applications, including take off and landing, the squadron must obey the longitudinal formation. In this work an algorithm is proposed to reconfigure the unmanned aircraft squadron between its latitudinal and circular formations. The algorithm is designed by using a new approach based on segments. The time complexity of the proposed algorithm is analyzed and its correction is proved. The proof of correction is confirmed by the simulations.

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References

  1. Lia, B., Huanga, K., Lia, J., Yuana, X.: “Analysis of influence of multiple uavs coordination system,”. J. Inf. Comput. Sci. 10(2), 571–578 (2013)

    Google Scholar 

  2. Cobano, J., Alejo, D., Vera, S., Heredia, G., Ollero, A.: Multiple gliding uav coordination for static soaring in real time applications. In: IEEE International Conference on Robotics and Automation (ICRA) (2013)

  3. Moon, S., Oh, E., Shim, D.H.: An integral framework of task assignment and path planning for multiple unmanned aerial vehicles in dynamic environments. J. Intell. Robot. Syst. 70(1–4), 303–313 (2013)

    Article  Google Scholar 

  4. Lin, L., Qibo, S., Shangguang, W., Fangchun, Y.: Research on pso based multiple uavs real-time task assignment. In: 25th Chinese Control and Decision Conference (CCDC), 2013, pp 1530–1536. IEEE (2013)

  5. Acevedo, J.J., Arrue, B.C., Maza, I., Ollero, A.: Distributed approach for coverage and patrolling missions with a team of heterogeneous aerial robots under communication constraints. Int. J. Adv. Robotic. Sy. 1–13(28) (2013)

  6. Acevedo, J.J., Arrue, B.C., Maza, I., Ollero, A.: Cooperative large area surveillance with a team of aerial mobile robots for long endurance missions. J. Intell. Robot. Syst. 70(1–4), 329–345 (2013)

    Article  Google Scholar 

  7. Pimenta, L.C., Pereira, G.A., Gonċalves, M.M., Michael, N., Turpin, M., Kumar, V.: Decentralized controllers for perimeter surveillance with teams of aerial robots. Adv. Robot. 27(9), 697–709 (2013)

    Article  Google Scholar 

  8. Mellinger, D., Michael, N., Kumar, V.: Trajectory generation and control for precise aggressive maneuvers with quadrotors. Int. J. Robot. Res. 31(5), 664–674 (2012)

    Article  Google Scholar 

  9. Mellinger, D., Kushleyev, A., Kumar, V.: Mixed-integer quadratic program trajectory generation for heterogeneous quadrotor teams. In: IEEE International Conference on Robotics and Automation (ICRA), 2012, pp. 477–483, IEEE (2012)

  10. Turpin, M., Michael, N., Kumar, V.: Trajectory design and control for aggressive formation flight with quadrotors. Auton. Robot. 33(1–2), 143–156 (2012)

    Article  Google Scholar 

  11. Neto, A.A., Macharet, D.G., Campos, M.F.: On the generation of trajectories for multiple uavs in environments with obstacles. In: Selected papers from the 2nd International Symposium on UAVs, June 8–10, 2009, pp. 123–141. Springer, Reno

  12. Chen, X., Lu, Z.Y., Zhang, J.: Cooperative search and path planning of multi-unmanned aerial vehicles in uncertain environment based on bayes theory. Appl. Mech. Mater. 336, 843–846 (2013)

    Article  Google Scholar 

  13. Kolling, A., Kleiner, A.: Multi-uav motion planning for guaranteed search. In: Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, International Foundation for Autonomous Agents and Multiagent Systems, pp. 79–86 (2013)

  14. George, J., Sujit, P., Sousa, J.B.: Search strategies for multiple uav search and destroy missions. J. Intell. Robot. Syst. 61(1–4), 355–367 (2011)

    Article  Google Scholar 

  15. Ragi, S., Chong, E.K.: Decentralized control of unmanned aerial vehicles for multitarget tracking. In: International Conference on Unmanned Aircraft Systems (ICUAS), 2013, pp. 260–268. IEEE (2013)

  16. Zhu, S., Wang, D.: Adversarial ground target tracking using uavs with input constraints. J. Intell. Robot. Syst. 65(1–4), 521–532 (2012)

    Article  MATH  Google Scholar 

  17. Zhu, S., Wang, D., Low, C.B.: Ground target tracking using uav with input constraints. J. Intell. Robot. Syst. 69(1–4), 417–429 (2013)

    Article  Google Scholar 

  18. Wei, Y., Blake, M.B., Madey, G.R.: An operation-time simulation framework for uav swarm configuration and mission planning. Procedia Comput. Sci. 18, 1949–1958 (2013)

    Article  Google Scholar 

  19. Kim, J., Song, B.D., Morrison, J.R.: On the scheduling of systems of uavs and fuel service stations for long-term mission fulfillment. J. Intell. Robot. Syst. 70(1–4), 347–359 (2013)

    Article  Google Scholar 

  20. You, D., Shim, D.: Autonomous formation flight test of multi-micro aerial vehicles. J. Intell. Robot. Syst. 61(1–4), 321–337 (2011)

    Article  Google Scholar 

  21. Zhang, M., Liu, H.H.: Formation flight of multiple fixed-wing unmanned aerial vehicles. In: American Control Conference (ACC), 2013, pp. 1614–1619, IEEE (2013)

  22. Guerrero, J.A., Garcia, P.C., Challal, Y.: Quadrotors formation control. J. Intell. Robot. Syst. 70(1–4), 221–231 (2013)

    Article  Google Scholar 

  23. Zhu, S., Wang, D., Low, C.: Cooperative control of multiple uavs for source seeking. J. Intell. Robot. Syst. 70(1–4), 293–301 (2013)

    Article  Google Scholar 

  24. Min, F.N.F.: Haibo; Sun, Decentralized uav formation tracking flight control using gyroscopic force. In: CIMSA 2009 - International Conference on Computational Intelligence for Measurement Systems and Applications. Hong-Kong, China (2009)

  25. Verma, A., Wu, C.-N., Castelli, V.: Uav formation command and control management. In: 2nd AIAA Unmanned Unlimited Conference and Workshop & Exhibit (2003)

  26. Chao, Z., Zhou, S.-L., Ming, L., Zhang, W.-G.: Uav formation flight based on nonlinear model predictive control. Math. Probl. Eng. 2012(261367), 1–15 (2012)

    Article  Google Scholar 

  27. He, L.-L., Lou, X.-C.: Study on the formation control methods for multi-agent based on geometric characteristics. In: Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (2013)

  28. El-Hawwary, M.I.: Distributed stabilization of 3d circular formations. In: European Control Conference (ECC). Zürich, Switzerland (2013)

  29. Ajorlou, A., Moezzi, K., Aghdam, A.G., Nersesov, S.G.: Two-stage time-optimal formation reconfiguration strategy. Syst. Control Lett. 62(6), 496–502 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  30. Duan, H., Luo, Q., Shi, Y., Ma, G.: Hybrid particle swarm optimization and genetic algorithm for multi-uav formation reconfiguration. IEEE Comput. Intell. Mag. 8(3), 16–27 (2013)

    Article  Google Scholar 

  31. Hafez, A.T., Marasco, A.J., Givigi, S.N., Beaulieu, A., Rabbath, C.A.: Encirclement of multiple targets using model predictive control. In: American Control Conference (ACC), 2013, pp. 3147–3152, IEEE (2013)

  32. Marasco, A.J., Givigi, S.N., Rabbath, C.A., Beaulieu, A.: Dynamic encirclement of a moving target using decentralized nonlinear model predictive control. In: American Control Conference (ACC), 2013, pp. 3960–3966, IEEE (2013)

  33. Sadraey, M.: Multi-vehicle circular formation flight in an unknown time-varying flow-field. In: International Conference on Unmanned Aircraft Systems (ICUAS), 2013, pp. 859–868, IEEE (2013)

  34. Ma, L., Hovakimyan, N.: Cooperative target tracking in balanced circular formation: multiple uavs tracking a ground vehicle. In: American Control Conference (ACC), 2013, pp. 5386–5391, IEEE (2013)

  35. Yoo, S.-M., Lee, S., Park, C., Park, S.-Y.: Spacecraft fueloptimal and balancing maneuvers for a class of formation reconfiguration problems. Adv. Space Res. 52(8), 1476–1488 (2013)

  36. Yang, H., Jiang, B., Cocquempot, V., Chen, M.: Spacecraft formation stabilization and fault tolerance: a state-varying switched system approach. Syst. Control Lett. 62(9), 715–722 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  37. Schlanbusch, R., Oland, E.: Spacecraft formation reconfiguration with dynamic collision avoidance. In: Aerospace Conference, 2013, pp. 1–12. IEEE (2013)

  38. Cho, H., Park, S.-Y., Yoo, S.-M., Choi, K.-H.: Analytical solution to optimal relocation of satellite formation flying in arbitrary elliptic orbits. Aerosp. Sci. Technol. 25(1), 161–176 (2013)

    Article  Google Scholar 

  39. wei Cai, W., ping Yang, L., wei Zhu, Y., wen Zhang, Y.: Optimal satellite formation reconfiguration actuated by inter-satellite electromagnetic forces. Acta Astronautica 89(0), 154–165 (2013)

    Article  Google Scholar 

  40. Nag, S., Summerer, L.: Behaviour based, autonomous and distributed scatter manoeuvres for satellite swarms. Acta Astronautica 82(1), 95–109 (2013)

    Article  Google Scholar 

  41. Zhao, S., Lin, F., Peng, K., Chen, B.M., Lee, T.H.: Finite-time stabilization of circular formations using bearing-only measurements. CoRR arXiv:1303.2409 (2013)

  42. Zhang, H.-T., Chen, Z., Yan, L., Yu, W.: Applications of collective circular motion control to multirobot systems. IEEE Trans. Control Syst. Technol. 21(4), 1416–1422 (2013)

    Article  Google Scholar 

  43. Guanghua, W., Deyi, L., Wenyan, G., Peng, J.: Study on formation control of multi-robot systems. In: 3rd International Conference on Intelligent System Design and Engineering Applications (ISDEA), 2013, pp. 1335–1339 (2013)

  44. Barfoot, T.D., Clark, C.M.: Motion planning for formations of mobile robots. Robot. Auton. Syst. 46(2), 65–78 (2004)

    Article  Google Scholar 

  45. Barfoot, T.D., Clark, C.M., Rock, S.M., D’Eleuterio, G.M.: Kinematic path-planning for formations of mobile robots with a nonholonomic constraint. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2002, vol. 3, pp. 2819–2824. IEEE (2002)

  46. Anderson, M.R., Robbins, A.C.: Formation flight as a cooperative game. Collection of Technical AIAA Guidance, Navigation, and Control Conference and Exhibit, vol. 10, pp. 244–251 (1998)

  47. Kanjanawanishkul, K.: Formation control of mobile robots: Survey. eng. ubu. ac. th, pp. 50–64 (2005)

  48. Tanenbaum, A.S.: Modern Operating Systems. Prentice-Hall (1992)

  49. Yang, T., Jin, Y.: Multi-agent rotating consensus without relative velocity measurements in three-dimensional space. Int. J. Robust Nonlinear Control. 23, 473–482 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  50. Saska, M., Krajnik, T., Vonasek, V., Vanek, P., Preucil, L.: Navigation, localization and stabilization of formations of unmanned aerial and ground vehicles. In: International Conference on Unmanned Aircraft Systems (ICUAS), 2013, pp. 831–840. IEEE (2013)

  51. Saska, M., Vonásek, V., Přeučil, L.: Trajectory planning and control for airport snow sweeping by autonomous formations of ploughs. J. Intell. Robot. Syst. 72(2), 239–261 (2013)

  52. Saska, M., Vonásek, V., Preucil, L.: Roads sweeping by unmanned multi-vehicle formations. In: IEEE International Conference on Robotics and Automation (ICRA), 2011, pp. 631–636. IEEE (2011)

  53. Giacomin, P.A.S., Hemerly, E.M.: Parallel simulation for autonomous aircraft squadrons using virtual structure and a 3d maneuvers scheme. In: 22nd International Congress of Mechanical Engineering (COBEM 2013). Ribeirão Preto - SP, Brazil (2013)

  54. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of the IEEE International Conference on Neural Networks, 1995, vol. 4, pp. 1942–1948 (1995)

  55. Xu, B., Wang, S., Gao, D., Zhang, Y., Shi, Z.: Command filter based robust nonlinear control of hypersonic aircraft with magnitude constraints on states and actuators. J. Intell. Robot. Syst. 73(1–4), 233–247 (2014)

    Article  Google Scholar 

  56. Xu, B., Wang, D., Wang, H., Zhu, S.: Adaptive neural control of a hypersonic vehicle in discrete time. J. Intell. Robot. Syst. 73(1–4), 219–231 (2014)

    Article  Google Scholar 

  57. Xu, B., Wang, D., Sun, F., Shi, Z.: Direct neural discrete control of hypersonic flight vehicle. Nonlinear Dyn. 70(1), 269–278 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  58. Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms. MIT Press, Cambridge (2009)

    MATH  Google Scholar 

  59. Giacomin, P.A.S., Hemerly, E.M.: Optimum parallelization for aircraft squadrons simulation using message passing and cooperative game based control. In: Anais do XIX Congresso Brasileiro de Automática, CBA 2012, (Campina Grande - PB, Brazil), pp. 1135–1142. DEE-UFCG (2012)

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Authors and Affiliations

  1. Departamento de Ciências Exatas e Tecnológicas, Universidade Estadual de Santa Cruz, Ilhéus-BA, Brazil

    Paulo André Sperandio Giacomin

  2. Technological Institute of Aeronautics, Systems and Control Department, Sāo José dos Campos-SP, Brazil

    Elder Moreira Hemerly

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  1. Paulo André Sperandio Giacomin
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  2. Elder Moreira Hemerly
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Correspondence to Paulo André Sperandio Giacomin.

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This project is supported by CAPES.

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Sperandio Giacomin, P.A., Hemerly, E.M. Reconfiguration Between Longitudinal and Circular Formations for Multi-UAV Systems by Using Segments. J Intell Robot Syst 78, 339–355 (2015). https://doi.org/10.1007/s10846-014-0063-4

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  • DOI: https://doi.org/10.1007/s10846-014-0063-4

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