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Stochastic strategies for patrolling a terrain with a synchronized multi-robot system

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  • Caraballo, Luis E.
  • Díaz-Báñez, José M.
  • Fabila-Monroy, Ruy
  • Hidalgo-Toscano, Carlos

Abstract

A group of cooperative aerial robots can be deployed to efficiently patrol a terrain, in which each robot flies around an assigned area and shares information with the neighbors periodically in order to protect or supervise it. To ensure robustness, previous works on these synchronized systems propose sending a robot to the neighboring area in case it detects a failure. In order to deal with unpredictability and to improve on the efficiency in the deterministic patrolling scheme, this paper proposes random strategies to cover the areas distributed among the agents. First, a theoretical study of the stochastic process is addressed in this paper for two metrics: the idle time, the expected time between two consecutive observations of any point of the terrain and the isolation time, the expected time that a robot is without communication with any other robot. After that, the random strategies are experimentally compared with the deterministic strategy adding another metric: the broadcast time, the expected time elapsed from the moment a robot emits a message until it is received by all the other robots of the team. The simulations show that theoretical results are in good agreement with the simulations and the random strategies outperform the behavior obtained with the deterministic protocol proposed in the literature.

Suggested Citation

  • Caraballo, Luis E. & Díaz-Báñez, José M. & Fabila-Monroy, Ruy & Hidalgo-Toscano, Carlos, 2022. "Stochastic strategies for patrolling a terrain with a synchronized multi-robot system," European Journal of Operational Research, Elsevier, vol. 301(3), pages 1099-1116.
    • Handle: RePEc:eee:ejores:v:301:y:2022:i:3:p:1099-1116
    DOI: 10.1016/j.ejor.2021.11.049
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    References listed on IDEAS

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    1. Evers, Lanah & Barros, Ana Isabel & Monsuur, Herman & Wagelmans, Albert, 2014. "Online stochastic UAV mission planning with time windows and time-sensitive targets," European Journal of Operational Research, Elsevier, vol. 238(1), pages 348-362.
    2. Sergey Bereg & Luis-Evaristo Caraballo & José-Miguel Díaz-Báñez & Mario A. Lopez, 2018. "Computing the k-resilience of a synchronized multi-robot system," Journal of Combinatorial Optimization, Springer, vol. 36(2), pages 365-391, August.
    3. Sergey Bereg & Andrew Brunner & Luis-Evaristo Caraballo & José-Miguel Díaz-Báñez & Mario A. Lopez, 2020. "On the robustness of a synchronized multi-robot system," Journal of Combinatorial Optimization, Springer, vol. 39(4), pages 988-1016, May.
    4. Alpern, Steve & Lidbetter, Thomas & Papadaki, Katerina, 2019. "Optimizing periodic patrols against short attacks on the line and other networks," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1065-1073.
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    Cited by:

    1. Boris V. Rumiantsev & Rasul A. Kochkarov & Azret A. Kochkarov, 2023. "Graph-Clustering Method for Construction of the Optimal Movement Trajectory under the Terrain Patrolling," Mathematics, MDPI, vol. 11(1), pages 1-13, January.

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