MULTI-ROBOT DYNAMIC FORMATION PATH PLANNING WITH IMPROVED POLYCLONAL ARTIFICIAL IMMUNE ALGORITHM

Lixia Deng, Xin Ma, Jason Gu, and Yibin Li

References

  1. [1] D. Luo, W. Xu, S. Wu, and Y. Ma, UAV formation flightcontrol and formation switch strategy, Proc International Conf.on Computer Science & Education, Washington, USA, 2013,264–269.
  2. [2] D. Luo, T. Zhou, and S. Wu, Obstacle avoidance and formationregrouping strategy and control for UAV formation flight, Proc.International Conf. on Control and Automation, Washington,USA, 2013, 1921–1926.
  3. [3] M. Saffarian and F. Fahimi, A model predictive framework forautonomous 3D formation flight of helicopter groups, Controland Intelligent Systems, 37(4), 2009, 220–226.
  4. [4] F. Fahimi, S. Rineesh, and C. Nataraj, Formation controllersfor underactuated surface vessels and zero dynamics stability,Control and Intelligent Systems, 36(3), 2008, 277–287.
  5. [5] Y.H. Chang, C.Y. Yang, W.S. Chan, and H.W. Lin, et al.,Adaptive fuzzy sliding-mode formation controller design formulti-robot dynamic systems, International Journal of FuzzySystems, 16(1), 2014, 121–131.
  6. [6] B. Wu, D. Wang, and E.K. Poh, Cyclic formation control forsatellite formation using local relative measurements, Controland Intelligent Systems, 40(1), 2012, 11.
  7. [7] M. Lemay, F. Michaud, D. Letourneau, and J.M. Valin, Au-tonomous initialization of robot formations, Proc. InternationalConf. on Robotics and Automation, IEEE, 2004, 3018–3023.
  8. [8] K. Yuan, Y. Li, and L.X. Fang, Multiple mobile robot sys-tems: A survey of recent work, International Journal of ActaAutomatica Sinica, 33(8), 2007, 785–794.
  9. [9] D.H. Ren and G.Z. Lu, Thinking in formation control, Journalof Control and Decision, 20(6), 2005, 601–606.
  10. [10] J.V. Gomez, A. Lumbier, S. Garrido, and L. Moreno, Plan-ning robot formations with fast marching square includinguncertainty conditions, Journal of Robotics and AutonomousSystems, 61(2), 2012, 137–152.
  11. [11] X.Q. Zhang, Y.Q. Huang, and G. Liu, Research on improvedleader-following formation method, Computer Engineering andDesign, 31(11), 2010, 2547–2549.
  12. [12] Y. Dai and S.G. Lee, The leader–follower formation control ofnonholonomic mobile robots, International Journal of Control,Automation and Systems, 10(2), 2012, 350–361.
  13. [13] H. Zhai, Z. Ji, and J. Gao, Formation control of multiple robotfishes based on artificial potential field and leader–followerframework, Proc. International Conf. on Control and Decision,Washington, USA, 2013, 2616–2620.
  14. [14] L. Deng, X. Ma, J. Gu, and Y. Li, Planning multi-robotformation with improved polyclonal artificial immune algo-rithm, Proc. International Conf. on Robotics and Biomimetics,Washington, USA, 2013, 982–987.
  15. [15] J.P. Desai, A graph theoretic approach for modeling mobilerobot team formations, Journal of Robotic Systems, 19(11),2002, 511–525.290
  16. [16] J.P. Desai, V. Kumar, and J.P. Ostrowski, Control of changesin formation for a team of mobile robots, Proc. InternationalConf. on Robotics and Automation, IEEE, 1999, 1556–1561.
  17. [17] J.P. Desai, J.P. Ostrowski, and V. Kumar, Modeling and controlof formations of nonholomic mobile robots, Transactions onRobotics and Automation, 17(6), 2001, 905–908.
  18. [18] A.K. Das, R. Fierro, V. Kumar, and J.P. Ostrowski, et al.,A vision-based formation control framework, Transactions onRobotics and Automation, IEEE, 18(5), 2002, 813–825.
  19. [19] R. Fierro, A.K. Das, V. Kumar, and J.P. Ostrowski, Hybridcontrol of formations of robots, Proc. International Conf. onRobotics and Automation, IEEE, 2001, 157–162.
  20. [20] W. Ren and N. Sorensen, Distributed coordination architecturefor multi-robot formation control, Robotics and AutonomousSystems, 56(4), 2008, 324–333.
  21. [21] R. Falconi, L. Sabattini, C. Secchi, and C. Fantuzzi, et al.,A graph-based collision-free distributed formation control strat-egy, Proc. 18th IFAC World Congress, Milano, Italy, 2011,6011–6016.
  22. [22] S. Monteiro and E. Bicho, Attractor dynamics approach toformation control: theory and application, Autonomous Robots,29(3–4), 2010, 331–355.
  23. [23] R.K. Chetty, M. Singaperumal, and T. Nagarajan, Distributedformation planning and navigation framework for wheeledmobile robots, Applied Sciences, 11(9), 2011, 1501–1509.
  24. [24] L. Deng, X. Ma, J. Gu, and Y. Li, Improved poly-clonal artifi-cial immune network for multi-robot dynamic path planning,Proc. International Conf. on Information and Automation,Washington, USA, 2013, 128–133.
  25. [25] G.C. Luh and W.W. Liu, An immunological approach to mobilerobot reactive navigation, Applied Soft Computing, 8(1), 2008,30–45.
  26. [26] L. Deng, X. Ma, J. Gu, and Y. Li, Mobile robot pathplanning using polyclonal-based artificial immune network,Journal of Control Science and Engineering, 2013, 2013, 1–13.doi: http://dx.doi.org/10.1155/2013/416715.

Important Links:

Go Back