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Path Planning for Multi-UAV Formation

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Abstract

This paper presents an efficient and feasible algorithm for the path planning problem of the multiple unmanned aerial vehicles (multi-UAVs) formation in a known and realistic environment. The artificial potential field method updated by the additional control force is used for establishing two models for the single UAV, which are the particle dynamic model and the path planning optimization model. The additional control force can be calculated by using the optimal control method. Furthermore, the multi-UAV path planning model is established by introducing “virtual velocity rigid body” and “virtual target point”. Then, the motion states of the lead plane and wingmen are obtained from the path planning model. Finally, the path following process based on the quadrotor helicopter PID controllers is introduced to verify the rationality of the path planning results. The simulation results show that the artificial potential method with the additional control force improved by the optimal control method has a good path planning ability for the single UAV and the all UAVs formation. At the same time, the path planning results are available and the UAVs can basically track the UAV formation.

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References

  1. Garcia, M., Viguria, A., Ollero, A.: Dynamic Graph-Search Algorithm for Global Path Planning in Presence of Hazardous Weather (2012)

  2. Khatib, O.: Real-time Obstacle Avoidance for Manipulators and Mobile Robots. Int. J. Robot. Res. 5 (1), 90–98 (1986)

    Article  MathSciNet  Google Scholar 

  3. Dunbar, W.B., Caveney, D.S.: Distributed Receding Horizon Control of Vehicle Platoons: Stability and String Stability. IEEE Trans. Autom. Control 57 (3), 620–633 (2012). doi:10.1109/TAC.2011.2159651

    Article  MathSciNet  Google Scholar 

  4. Pei, L., HaiBin, D.: Path Planning of Unmanned Aerial Vehicle Based on Improved Gravitational Search Algorithm. Sci. China Technol. Sci. 55 (10), 2712–2719 (2012). doi:10.1007/s11431-012-4890-x

    Article  Google Scholar 

  5. Roberge, V., Tarbouchi, M., Labonte, G.: Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-time UAV Path Planning. IEEE Trans. Ind. Inform. 9 (1), 132–141 (2013). doi:10.1109/TII.2012.2198665

    Article  Google Scholar 

  6. Anderson, B.D.O., Yu, C., Baris, F.: Information Architecture and Control Design for Rigid Formations. In: 26th Chinese Control Conference, 26-31 July 2007, Piscataway, NJ, USA 2007. Proceedings of the 26th Chinese Control Conference. IEEE (2007)

  7. Xiaohua, W., Yadav, V., Balakrishnan, S.N.: Cooperative UAV Formation Flying with Obstacle/Collision Avoidance. IEEE Trans. Control Syst. Technol. 15 (4), 672–679 (2007). doi:10.1109/TCST.2007.899191

    Article  Google Scholar 

  8. Das, A.K., Fierro, R., Kumar, V., Ostrowski, J.P., Spletzer, J., Taylor, C.J.: A Vision-based Formation Control Framework. IEEE Trans. Robot. Autom. 18 (5), 813–825 (2002). doi:10.1109/TRA.2002.803463

    Article  Google Scholar 

  9. Chang Boon, L.: A Dynamic Virtual Structure Formation Control for Fixed-wing UAVs. In: 2011 9th IEEE International Conference on Control and Automation (ICCA 2011), 19-21 Dec. 2011, Piscataway, NJ, USA. IEEE (2011)

  10. McInnes, C.R.: Velocity Field Path-planning for Single and Multiple Unmanned Aerial Vehicles. Aeronaut. J. 107 (1073), 419–426 (2003)

    Google Scholar 

  11. Bemporad, A., Rocchi, C.: Decentralized Linear Time-varying Model Predictive Control of a Formation of Unmanned Aerial Vehicles. In: 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011), 12-15 Dec. 2011, Piscataway, NJ, USA, 7488–7493 (2011). IEEE

  12. Chen Y.-b., Luo G.-c., Mei Y.-s., Yu J.-q., Su X.-l.: UAV path planning using artificial potential field method updated by optimal control theory. Int. J. Syst. Sci. (2014). doi:10.1080/00207721.2014.929191

  13. Cetin, O., Zagli, I., Yilmaz, G.: Establishing Obstacle and Collision Free Communication Relay for UAVs with Artificial Potential Fields. J. Intell. Robot. Syst. 69 (1-4), 361–372 (2013)

    Article  Google Scholar 

  14. Charifa, S., Bikdash, M.: Comparison of geometrical, kinematic, and dynamic performance of several potential field methods. In: IEEE SoutheastCon 2009, 5-8 March 2009, Piscataway, NJ, USA. IEEE (2009)

  15. Luo, G.-c., Yu, J.-q., Zhang, S.-y., Zhang, W.: Artificial Potential Field based Receding Horizon Control for path planning. In: 2012 24th Chinese Control and Decision Conference (CCDC), 23-25 May 2012, Piscataway, NJ, USA. IEEE (2012)

  16. Zhang, X., Duan, H., Yu, Y.: Receding Horizon Control for Multi-UAVs Close Formation Control Based on Differential Evolution. Sci. China Ser. F (Inf. Sci.) 53 (2), 223–235 (2010). doi:10.1007/s11432-010-0036-6

    Google Scholar 

  17. Yanyang, W., Tietao, W., Xiangju, Q.: Study of Multi-objective Fuzzy Optimization for Path Planning. Chin. J. Aeronaut. 25 (1), 51–56 (2012). doi:10.1016/S1000-9361(11)60361-0

    Article  Google Scholar 

  18. Hua, S., You, Y., Zhang, H., Song, H.: Receding Horizon Control of UAV Formations. Electron. Opt. Control. 19 (3), 1–5 (2012)

    Google Scholar 

  19. Wu, S.: Optimal Control Theory and Application. China Machine Press, Beijing (2008)

    Google Scholar 

  20. Xie, L.-j., Xie, G.-r., Chen, H.-w., Li, X.-l.: Solution to Reinforcement Learning Problems with Artificial Potential Field. J. Cent. South Univ. Technol. 15 (4), 552–557 (2008). doi:10.1007/s11771-008-0104-

    Article  MathSciNet  Google Scholar 

  21. Mohamed, H.A., Yang, S., Moghavvemi, M.: Sliding Mode Controller Design for a Flying Quadrotor with Simplified Action Planner. In: ICCAS-SICE, 2009. IEEE (2009)

  22. Bouabdallah, S., Siegwart, R.: Full Control of a Quadrotor. In: 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 29 Oct.-2 Nov. 2007, Piscataway, NJ, USA 2007. IEEE (2007)

  23. Bai, Y., Liu, H., Shi, Z., Zhong, Y.: Robust Flight Control of Quadrotor Unmanned Air Vehicles. Jiqiren/Robot 34 (5), 519–524 (2012). doi:10.3724/SP.J.1218.2012.00519

    Google Scholar 

  24. Salih, A.L., Moghavvemi, M., Mohamed, H.A., Gaeid, K.S.: Modelling and PID Controller Design for a Quadrotor Unmanned air Vehicle. In: Automation Quality and Testing Robotics (AQTR), 2010 IEEE International Conference on. IEEE (2010)

  25. Efe, M.Ö.: Neural Network Assisted Computationally Simple PID Control of a Quadrotor UAV. IEEE Trans. Ind. Informat. 7 (2), 354–361 (2011)

    Article  Google Scholar 

  26. Koren, Y., Borenstein, J.: Potential Field Methods and their Inherent Limitations for Mobile robot navigation. In: Robotics and Automation, 1991. Proceedings., 1991 IEEE International Conference on. IEEE (1991)

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Authors and Affiliations

  1. School of Aerospace Engineering, Beijing Institute of Technology, Beijing, 100081, China

    YongBo Chen, JianQiao Yu, XiaoLong Su & GuanChen Luo

  2. Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, Beijing, 100081, China

    YongBo Chen, JianQiao Yu, XiaoLong Su & GuanChen Luo

Authors
  1. YongBo Chen
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  2. JianQiao Yu
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  3. XiaoLong Su
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  4. GuanChen Luo
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Correspondence to JianQiao Yu.

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Chen, Y., Yu, J., Su, X. et al. Path Planning for Multi-UAV Formation. J Intell Robot Syst 77, 229–246 (2015). https://doi.org/10.1007/s10846-014-0077-y

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  • DOI: https://doi.org/10.1007/s10846-014-0077-y

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