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Coordinated Convoy Protection Among Teams of Unmanned Aerial Vehicles

  • Magnus Egerstedt
  • Amir Rahmani
  • Shin-Yih (Ryan) Young
Reference work entry

Abstract

This chapter investigates how to control and coordinate teams of unmanned aerial vehicles (UAVs) to provide protection to convoys of ground vehicles. This is a rich yet canonical problem when coordinatingmultiple UAVs in that coordinated movements, task assignments, and resource balancing must all be performed for a successful completion of the mission. Time-optimal paths for providing convoy-protection to stationary ground vehicles are presented, and these algorithms are extended to moving ground vehicles. The assignment problems, associated with dispatching UAVs from the convoy to inspect and clear potential threats, are moreover discussed.

Keywords

Fuel Consumption Optimal Path Selection Policy Ground Vehicle Motion Primitive 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. P. Agarwal, T. Biedl, S. Lazard, S. Robbins, S. Suri, S. Whitesides, Curvature-constrained shortest paths in a convex polygon, in Proceedings of the ACM Symposium on Computational Geometry, Minneapolis, 1998, pp. 392–401Google Scholar
  2. A. Arsie, K. Savla, E. Frazzoli, Efficient routing algorithms for multiple vehicles with no explicit communications. IEEE Trans. Autom. Control 54(10), 2302–2317 (2009)CrossRefMathSciNetGoogle Scholar
  3. G. Arslan, J.R. Marden, J.S. Shamma, Autonomous vehicle-target assignment: a game theoretical formulation. ASME J. Dyn. Syst. Meas. Control 129(5), 584–596 (2007)CrossRefGoogle Scholar
  4. R.W. Beard, T.W. McLain, M.A. Goodrich, E.P. Anderson, Coordinated target assignment and intercept for unmanned air vehicles. IEEE Trans. Rob. Autom. 18(6), 911–922 (2002)CrossRefGoogle Scholar
  5. R. Beard, T. McLain, D. Nelson, D. Kingston, Decentralized cooperative aerial surveillance using fixed-wing miniature UAVs. IEEE Proc. 94(7), 1306–1324 (2006)CrossRefGoogle Scholar
  6. C. Belta, A. Bicchi, M. Egerstedt, E. Frazzoli, E. Klavins, G.J. Pappas, Symbolic planning and control of robot motion: state of the art and grand challenges. IEEE Rob. Autom. Mag. 14(1), 61–70 (2007)CrossRefGoogle Scholar
  7. J. Boissonnat, A. Cérézo, J. Leblond, Shortest paths of bounded curvature in the plane. J. Intell. Rob. Syst. 11(1–2), 5–20 (1994)CrossRefzbMATHGoogle Scholar
  8. R.E. Burkard, Selected topics in assignment problems. Discret. Appl. Math. 123 , 257–302 (2002)CrossRefzbMATHMathSciNetGoogle Scholar
  9. H. Chitsaz, S.M. LaValle, Time-optimal paths for a Dubins airplane, in IEEE Conference on Decision and Control, New Orleans, 2007, pp. 2379–2384Google Scholar
  10. D. Cruz, J. McClintock, B. Perteet, O. Orqueda, Y. Cao, R. Fierro, Decentralized cooperative control – a multivehicle platform for research in networked embedded systems. IEEE Control Syst. 27(3), 58–78 (2007)CrossRefGoogle Scholar
  11. X.C. Ding, A. Rahmani, M. Egerstedt, Optimal multi-UAV convoy protection, in International Conference on Robot Communication and Coordination, Odense, 2009Google Scholar
  12. X.C. Ding, A. Rahmani, M. Egerstedt, Multi-UAV convoy protection: an optimal approach to path planning and coordination. IEEE Trans. Rob. 26(2), 256–268 (2010)CrossRefGoogle Scholar
  13. L. Dubins, On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents. Am. J. Math. 79, 497–516 (1957)CrossRefzbMATHMathSciNetGoogle Scholar
  14. L. Dubins, On plane curves with curvature. Pac. J. Math. 11(2), 471–481 (1961)CrossRefzbMATHMathSciNetGoogle Scholar
  15. M. Egerstedt, Interface Control Document for Heterogeneous Multi-vehicle Ground Convoy Protection (Georgia Institute of Technology, Atlanta, 2011)Google Scholar
  16. E. Frazzoli, M.A. Dahleh, E. Feron, Maneuver-based motion planning for nonlinear systems with symmetries. IEEE Trans. Rob. 21(6), 1077–1091 (2005)CrossRefGoogle Scholar
  17. M.R. Garey, D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness (Freeman, SanFrancisco, 1979)zbMATHGoogle Scholar
  18. A. R. Girard, A.S. Howell, J.K. Hedrick, Border patrol and surveillance missions using multiple unmanned air vehicles, in IEEE Conference on Decision and Control, Atlantis, Bahamas, 2004, pp. 620–625Google Scholar
  19. B. Grocholsky, J. Keller, V. Kumar, G. Pappas, Cooperative air and ground surveillance: a scalable approach to the detection and localization of targets by a network of UAVs and UGVs. IEEE Rob. Autom. Mag. 13(3) 16–26 (2006)CrossRefGoogle Scholar
  20. K. Hauser, T. Bretl, K. Harada, J.C. Latombe, Using motion primitives in probabilistic sample-based planning for humanoid robots, in In Workshop on the Algorithmic Foundations of Robotics (WAFR), New York, 2006Google Scholar
  21. M. Ji, S. Azuma, M. Egerstedt, Role-assignment in multi-agent coordination. Int. J. Assist. Rob. Mechatron. 7(1), 32–40 (2006)Google Scholar
  22. D.E. Kirk, Optimal Control Theory, An Introduction (Dover, Mineola, 2004)Google Scholar
  23. H.W. Kuhn, The hungarian method for the assignment problem. Naval Res. Logist. Q. 2, 83–97 (1955)CrossRefGoogle Scholar
  24. S.M. Lavalle, Planning Algorithms (Cambridge University Press, New York, 2006)CrossRefzbMATHGoogle Scholar
  25. J. Lee, R. Huang, A. Vaughn, X. Xiao, J.K. Hedrick, M. Zennaro, R. Sengupta, Strategies of path- planning for a UAV to track a ground vehicle, in The Second Annual Symposium on Autonomous Intelligent Networks and Systems, Menlo Park, 2003Google Scholar
  26. T.G. McGee, S. Spry, J.K. Hedrick, Optimal path planning in a constant wind with a bounded turning rate, in AIAA Guidance, Navigation, and Control Conference and Exhibit, San Francisco, 2005Google Scholar
  27. B. Moore, K. Passino, Distributed balancing of AAVs for uniform surveillance coverage, in IEEE Conference on Decision and Control, Seville, 2005, pp. 7060–7065Google Scholar
  28. S. Morris, M. Holden, Design of micro air vehicles and flight test validation, in Proceedings of the Fixed, Flapping and Rotary Wing Vehicles at Very Low Reynolds Numbers, Notre Dame, 2000, pp. 153–176Google Scholar
  29. Northrop Grumman, Heterogeneous Aerial Reconnaissance Team (HART), http://en.wikipedia.org/wiki/Heterogeneous_Aerial_Reconnaissance_Team
  30. P.M. Pardalos, F. Rendl, H. Wolkowicz, The quadratic assignment problem, in The Quadratic Assignment and Related Problems, ed. by P.M. Pardalos, H. Wolkowicz. DIMACS Series, vol. 16 (American Mathematical Society, Providence, 1994), pp. 1–41.Google Scholar
  31. M. Pavone, E. Frazzoli, F. Bullo, Adaptive and distributed algorithms for vehicle routing in a stochastic and dynamic environment. IEEE Trans. Autom. Control 54(10), 2302–2317 (2009)CrossRefGoogle Scholar
  32. S. Ponda, J. Redding, H.L. Choi, J.P. How, M. Vavrina, J. Vian, Decentralized planning for complex missions with dynamic communication constraints, in American Control Conference, Baltimore, Maryland, 2010Google Scholar
  33. H. Psaraftis, Dynamic vehicle routing problems, in Vehicle Routing: Methods and Studies, ed. by B. Golden, A. Assad. Studies in Management Science and Systems (Elsevier, Amsterdam, 1988)Google Scholar
  34. M. Quigley, M.A. Goodrich, S. Griffiths, A. Eldredge, R.W. Beard, Target acquisition, localization, and surveillance using a fixed-wing, mini-UAV and gimbaled camera. International Conference on Robotics and Automation, Barcelona, 2005, pp. 18–22lGoogle Scholar
  35. J. Reeds, L. Shepp (1990) Optimal paths for a car that goes both forwards and backwards. Pac. J. Math. 145(2), 367–393CrossRefMathSciNetGoogle Scholar
  36. A. Richards, J. Bellingham, M. Tillerson, J. How, Coordination and control of multiple UAVs, in Proceedings of the AIAA Conference on Guidance, Navigation, and Control, Monterey, 2002Google Scholar
  37. K. Savla, E. Frazzoli, F. Bullo, Traveling salesperson problems for the Dubins vehicle. IEEE Trans. Autom. Control 53(6), 1378–1391 (2008)CrossRefMathSciNetGoogle Scholar
  38. C. Schumacher, P.R. Chandler, S.J. Rasmussen, D. Walker, Task allocation for wide area search munitions with variable path length, in Proceedings of the American Control Conference, Denver, 2003, pp. 3472–3477Google Scholar
  39. P. Souèeres, J. Boissonnat, Optimal trajectories for nonholonomic mobile robots, in Robot Motion Planning and Control (Springer, London, 1998), pp. 93–170CrossRefGoogle Scholar
  40. P. Souèeres, J. Laumond, Shortest paths synthesis for a car-like robot. IEEE Trans. Autom. Control 41(5), 672–688 (1996)CrossRefMathSciNetGoogle Scholar
  41. S.C. Spry, A.R. Girard, J.K. Hedrick, Convoy protection using multiple unmanned air vehicles: organization and coordination, in American Control Conference, Portland, 2005Google Scholar
  42. G.C. Walsh, R. Montgomery, S. Sastry, Optimal path planning on matrix Lie groups. IEEE Conf. Decis. Control 2(14–16), 1258–1263 (1994)Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaUSA
  2. 2.Department of Mechanical and Aerospace EngineeringUniversity of MiamiCoral GablesUSA
  3. 3.Advanced Technology Center, Rockwell CollinsRockwell CollinsIAUSA

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