Journal of Intelligent & Robotic Systems

, Volume 74, Issue 1–2, pp 269–285 | Cite as

One-to-One Coordination Algorithm for Decentralized Area Partition in Surveillance Missions with a Team of Aerial Robots

  • Jose J. Acevedo
  • Begoña C. Arrue
  • Jose Miguel Diaz-Bañez
  • Inmaculada Ventura
  • Ivan Maza
  • Anibal Ollero


This paper presents a decentralized algorithm for area partition in surveillance missions that ensures information propagation among all the robots in the team. The robots have short communication ranges compared to the size of the area to be covered, so a distributed one-to-one coordination schema has been adopted. The goal of the team is to minimize the elapsed time between two consecutive observations of any point in the area. A grid-shape area partition strategy has been designed to guarantee that the information gathered by any robot is shared among all the members of the team. The whole proposed decentralized strategy has been simulated in an urban scenario to confirm that fulfils all the goals and requirements and has been also compared to other strategies.


Monitoring missions Synchronization Multi-UAV system Coordination Decentralized system 


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  1. 1.
    Acevedo, J.J., Arrue, B., Maza, I., Ollero, A.: Distributed approach for coverage and patrolling missions with a team of heterogeneous aerial robots under communication constraints. Int. J. Adv. Robot. Syst. 10(28), 1–13 (2013)Google Scholar
  2. 2.
    Acevedo, J.J., Arrue, B.C., Diaz-Banez, J.M., Ventura, I., Maza, I., Ollero, A.: Decentralized strategy to ensure information propagation in area monitoring missions with a team of uavs under limited communications. In: 2013 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 565–574 (2013)Google Scholar
  3. 3.
    Acevedo, J.J., Arrue, B.C., Maza, I., Ollero, A.: Cooperative perimeter surveillance with a team of mobile robots under communication constraints. In: International Conference on Intelligent Robots and Systems (2013)Google Scholar
  4. 4.
    Acevedo, J.J., Begoña A.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, 329–345 (2013)CrossRefGoogle Scholar
  5. 5.
    Agmon, N., Kaminka, G.A., Kraus, S.: Multi-robot adversarial patrolling: facing a full-knowledge opponent. J. Artif. Int. Res. 42(1), 887–916 (2011)MATHMathSciNetGoogle Scholar
  6. 6.
    Baseggio, M., Cenedese, A., Merlo, P., Pozzi, M., Schenato, L.: Distributed perimeter patrolling and tracking for camera networks. In: 2010 49th IEEE Conference on Decision and Control (CDC), pp. 2093–2098 (2010)Google Scholar
  7. 7.
    Bereg, S., Díaz-Báñez, J.M., Fort, M., Pérez-Lantero, P., Lopez, M.A., Urrutia, J., Ventura, I.: Cooperative surveillance with high-quality communication. Internal report (2012)Google Scholar
  8. 8.
    Carli, R., Cenedese, A., Schenato, L.: Distributed partitioning strategies for perimeter patrolling. In: American Control Conference (ACC), 2011, pp. 4026–4031, June 29 2011–July 1 2011Google Scholar
  9. 9.
    Chevaleyre, Y.: Theoretical analysis of the multi-agent patrolling problem. In: IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2004. (IAT 2004). Proceedings, pp. 302–308 (2004)Google Scholar
  10. 10.
    Choset, H., Pignon, P.: Coverage path planning: the boustrophedon decomposition. In: International Conference on Field and Service Robotics (1997)Google Scholar
  11. 11.
    Elmaliach, Y., Shiloni, A., Kaminka, G.A.: A realistic model of frequency-based multi-robot polyline patrolling. In: Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems - vol. 1, AAMAS ’08, pp. 63–70, Richland, SC. International Foundation for Autonomous Agents and Multiagent Systems (2008)Google Scholar
  12. 12.
    Garey, M.R., Johnson, D.S.: Computers and Intractability; A Guide to the Theory of NP-Completeness. W. H. Freeman & Co., New York (1990)Google Scholar
  13. 13.
    Guruprasad, K.R., Wilson, Z., Dasgupta, P.: Complete coverage of an initially unknown environment by multiple robots using voronoi partition. In: International Conference on Advances in Control and Optimization in Dynamical Systems (2012)Google Scholar
  14. 14.
    Hadlock, F.: Finding a maximum cut of a planar graph in polynomial time. SIAM J. Comput. 4, 221–225 (1975)CrossRefMATHMathSciNetGoogle Scholar
  15. 15.
    Hazon, N., Kaminka, G.A.: On redundancy, efficiency, and robustness in coverage for multiple robots. Robot. Auton. Syst. 56(12), 1102–1114 (2008)CrossRefGoogle Scholar
  16. 16.
    Heredia, G., Caballero, F., Maza, I., Merino, L., Viguria, A., Ollero, A.: Multi-unmanned aerial vehicle (UAV) cooperative fault detection employing differential global positioning (DGPS), inertial and vision sensors. Sensors 9(9), 7566–7579 (2009)CrossRefGoogle Scholar
  17. 17.
    Kingston, D., Beard, R.W., Holt, R.S.: Decentralized perimeter surveillance using a team of UAVs. IEEE Trans. Robot. 24(6), 1394–1404 (2008)CrossRefGoogle Scholar
  18. 18.
    Maza, I., Caballero, F., Capitan, J., Martinez de Dios, J.R., Ollero, A.: A distributed architecture for a robotic platform with aerial sensor transportation and self-deployment capabilities. J. Field Robot. 28(3), 303–328 (2011)CrossRefGoogle Scholar
  19. 19.
    Ollero, A., Maza, I. (eds.): Multiple heterogeneous unmanned aerial vehicles. Springer Tracts on Advanced Robotics. Springer-Verlag (2007)Google Scholar
  20. 20.
    Pasqualetti, F., Durham, J.W., Bullo, F.: Cooperative patrolling via weighted tours: performance analysis and distributed algorithms. IEEE Trans. Robot. 28(5), 1181–1188 (2012)CrossRefGoogle Scholar
  21. 21.
    Pasqualetti, F., Franchi, A., Bullo, F.: On cooperative patrolling: optimal trajectories, complexity analysis, and approximation algorithms. IEEE Trans. Robot. 28(3), 592–606 (2012)CrossRefGoogle Scholar
  22. 22.
    Smith, S.L., Rus, D.: Multi-robot monitoring in dynamic environments with guaranteed currency of observations. In: 2010 49th IEEE Conference on Decision and Control (CDC), pp. 514–521 (2010)Google Scholar
  23. 23.
    Viguria, A., Maza, I., Ollero, A.: Distributed service-based cooperation in aerial/ground robot teams applied to fire detection and extinguishing missions. Adv. Robot. 24(1–2), 1–23 (2010)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Jose J. Acevedo
    • 1
  • Begoña C. Arrue
    • 1
  • Jose Miguel Diaz-Bañez
    • 2
  • Inmaculada Ventura
    • 2
  • Ivan Maza
    • 1
  • Anibal Ollero
    • 1
  1. 1.Grupo de Robotica, Visión y ControlUniversidad de SevillaSevillaSpain
  2. 2.Dpto. de Matemática Aplicada IIUniversidad de SevillaSevillaSpain

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