Yu Wang, Shuo Wang, Min Tan, and Junzhi Yu


  1. [1] I. Sa, S. Hrabar, and P. Corke, Inspection of pole-like structures using a vision-controlled VTOL UAV and shared autonomy, Proc. IEEE/RSJ Int. Conf. Intell. Robots Syst., Chicago, IL, 2014, 4819–4826.
  2. [2] S. Islam, X.P. Liu, and A.E. Saddik, Adaptive sliding mode control of unmanned four rotor flying vehicle, International Journal of Robotics and Automation, 30(2), 2015.
  3. [3] Y. Lin, J. Hyyppa, T. Rosnell, A. Jaakkola, and E. Honkavaara, Development of a UAV-MMS-collaborative aerial-to-ground remote sensing system – a preparatory field validation, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6(4), 2013, 1893–1898.
  4. [4] V. Sharma and R. Kumar, A cooperative network framework for multi-UAV guided ground ad hoc networks, Journal of Intelligent and Robotic Systems, 77(3–4), 2015, 629–652.
  5. [5] J. Ni, X. Yang, J. Chen, and S.X. Yang, Dynamic bioinspired network for multi-robot formation control in unknown environments, International Journal of Robotics and Automation, 30(3), 2015.
  6. [6] A. Yang, W. Naeem, G.W. Irwin, and K. Li, Stability analysis and implementation of a decentralized formation control strategy for unmanned vehicles, IEEE Transactions on Control Systems Technology, 22(2), 2014, 706–720.
  7. [7] X. Dong, B. Yu B, Z. Shi, and Y. Zhong, Time-varying formation control for unmanned aerial vehicles: theories and applications, IEEE Transactions on Control Systems Technology, 23(1), 2015, 340–348.
  8. [8] F. Liao, X. Dong, and F. Lin, Robust formation and reconfiguration control of multiple VTOL UAVs: design and flight test, Proc. 22nd Mediterranean Conference of Control and Automation, Palermo, Italy, 2014, 1440–1445.
  9. [9] T. Paul, T.R. Krogstad, and J.T. Gravdahl, UAV formation flight using 3D potential field, Proc. 16th Mediterranean Conf. Control Automation, Ajaccio, France, 2008, 1240–1245.
  10. [10] Z. Kan, L. Navaravong, J.M. Shea, E.L. Pasiliao, and W.E. Dixon, Graph matching-based formation reconfiguration of networked agents with connectivity maintenance. IEEE Transactions on Control of Network Systems, 2(1), 2015, 24–35.
  11. [11] T. Lee, M. Leok, and N.H. McClamroch, A combinatorial optimal control problem for spacecraft formation reconfiguration, Proc. 46th IEEE Conference on Decision and Control, 2007, 5370–5375.
  12. [12] T. Furukawa, H.F. Durrant-Whyte, F. Bourganlt, and G. Dissanayake, Time-optimal coordinated control of the relative formation of multiple vehicles, Proc. IEEE Int. Symp. Computational Intelligence Robotics Automation, Kobe, 2003, 259–264.
  13. [13] G.T. Huntington and A.V. Rao, Optimal reconfiguration of spacecraft formations using the Gauss pseudospectral method, 367 Journal of Guidance, Control, and Dynamics, 31(3), 2008, 689–698.
  14. [14] B. Acikmese, D.P. Scharf, E.A. Murray, and Y.H. Fred, A convex guidance algorithm for formation reconfiguration, Proc. of the AIAA Guidance, Navigation, and Control Conference and Exhibit, 2006.
  15. [15] X. Zhang, H. Duan, and C. Yang, Pigeon-inspired optimization approach to multiple UAVs formation reconfiguration controller design, Proc. IEEE Chinese Guidance, Navigation and Control Conference (CGNCC), Yantai, China, 2014, 2707–2712.
  16. [16] H. Duan, G. Ma, and D. Luo. Optimal formation reconfiguration control of multiple UCAVs using improved particle swarm optimization, Journal of Bionic Engineering, 5(4), 2008, 340–347.
  17. [17] C. Sun, H. Duan, and Y. Shi. Optimal satellite formation reconfiguration based on closed-loop brain storm optimization, IEEE Computational Intelligence Magazine, 8(4), 2013, 39–51.
  18. [18] A. Zhu and S.X. Yang, Tracking control of a mobile robot with stability analysis, International Journal of Robotics and Automation, 28(4), 2013, 340–348.
  19. [19] A. Zhu and S.X. Yang, An improved approach to dynamic task assignment of non-holonomic multi-robots, International Journal of Robotics and Automation, 26(4), 2011, 362–368.
  20. [20] M. Shanmugavel, A. Tsourdos, B.A. White, and R. Zbikowski, Co-operative path planning of multiple UAVs using Dubins paths with clothoid arcs, Control Engineering Practice, 18(9), 2010, 1084–1092.
  21. [21] M. Shanmugavel, A. Tsourdos, R. Zbikowski, B.A. White, C.A. Rabbath, and N. Lechevin, A solution to simultaneous arrival of multiple UAVs using Pythagorean Hodograph curves, Proc. American Control Conf., Minneapolis, MN, USA, 2006.
  22. [22] R. Dai and J.E. Cochran, Path planning for multiple unmanned aerial vehicles by parameterized cornu-spirals, Proc. American Control Conf., St. Louis, MO, USA, 2009, 2391–2396.
  23. [23] G. Ambrosino, M. Ariola, U. Ciniglio, F. Corraro, E. De Lellis, and A. Pironti, Path generation and tracking in 3-D for UAVs, IEEE Transactions on Control Systems Technology, 17(4), 2009, 980–988.
  24. [24] A. Kumar and A. Ojha, Subdivision-based corridor map method path planning, International Journal of Robotics and Automation, 28(4), 2013.
  25. [25] M. Chang and J. Chou, A novel machine vision-based mobile robot navigation system in an unknown environment, International Journal of Robotics and Automation, 25(4), 2010, 344–351.
  26. [26] L.E. Dubins, On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents, Journal of Mathematics, 79(3), 1957, 497–516.
  27. [27] Y. Wang, S. Wang, M. Tan, and Q. Wei, Real-time dynamic Dubins-Helix method for 3-D trajectory smoothing, IEEE Transactions on Control Systems Technology, 23(2), 2015, 730–736.
  28. [28] Y. Wang, S. Wang, and M. Tan, Path generation of autonomous approach to a moving ship for unmanned vehicles, IEEE Transactions on Industrial Electronics, 62(9), 2015, 5619–5629.

Important Links:

Go Back