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Algorithms for Multi-agent Interaction in the Distribution of Robots in a Group Between Work Areas in Long-Term Monitoring Tasks

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Informatics and Cybernetics in Intelligent Systems (CSOC 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 228))

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Abstract

The article is devoted to the problem of long-term monitoring of vast territories and water areas by groups of mobile robots in order to timely prevent dangerous consequences of man-made or natural accidents. A group of robots starts from the base and begins collecting data from several work areas. For this, the group must be divided into subgroups according to the number of work areas. Some of the group’s robots remain in reserve at the base. When a robot runs out of energy, it can be replaced by another robot of the subgroup, or a robot from the reserve. In this paper, we propose a method and algorithms for the distribution of robots in a group into subgroups based on the multi-agent interaction of agents in working areas and agents of mobile robots. The differences between homogeneous and heterogeneous groups of robots are taken into account. The results of experimental studies are presented.

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References

  1. Dunbabin, M., Marques, L.: Robots for environmental monitoring: Significant advancements and applications. IEEE Robot. Autom. Mag. 19, 24–39 (2012)

    Article  Google Scholar 

  2. Bogue, R.: Robots for monitoring the environment. Ind. Robot An Int. J. 38, 560–566 (2011). https://doi.org/10.1108/01439911111179066

    Article  Google Scholar 

  3. Marques, L., Martins, A., de Almeida, A.T.: Environmental monitoring with mobile robots. In: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3624–3629 (2005)

    Google Scholar 

  4. Marchant, R., Ramos, F.: Bayesian optimisation for intelligent environmental monitoring. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2242–2249 (2012)

    Google Scholar 

  5. Trincavelli, M., Reggente, M., Coradeschi, S., Loutfi, A., Ishida, H., Lilienthal, A.J.: Towards environmental monitoring with mobile robots. In: 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2210–2215 (2008)

    Google Scholar 

  6. Bayat, B., Crasta, N., Crespi, A., Pascoal, A.M., Ijspeert, A.: Environmental monitoring using autonomous vehicles: a survey of recent searching techniques. Curr. Opin. Biotechnol. 45, 76–84 (2017)

    Article  Google Scholar 

  7. He, X., et al.: Autonomous chemical-sensing aerial robot for urban/suburban environmental monitoring. IEEE Syst. J. 13, 3524–3535 (2019)

    Article  Google Scholar 

  8. Tekdas, O., Isler, V., Lim, J.H., Terzis, A.: Using mobile robots to harvest data from sensor fields. IEEE Wirel. Commun. 16, 22–28 (2009)

    Article  Google Scholar 

  9. Lu, Q., Han, Q.-L.: Mobile robot networks for environmental monitoring: a cooperative receding horizon temporal logic control approach. IEEE Trans. Cybern. 49, 698–711 (2018)

    Article  Google Scholar 

  10. Ivanov, D.: Fog robotics distributed computing in a monitoring task. In: Computer Science On-line Conference, pp. 554–562 (2020)

    Google Scholar 

  11. Carpentiero, M., Gugliermetti, L., Sabatini, M., Palmerini, G.B.: A swarm of wheeled and aerial robots for environmental monitoring. In: 2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC), pp. 90–95 (2017)

    Google Scholar 

  12. Schwager, M., McLurkin, J., Slotine, J.-J.E., Rus, D.: From theory to practice: distributed coverage control experiments with groups of robots. In: Experimental Robotics, pp. 127–136 (2009)

    Google Scholar 

  13. Abbas, M.Z., et al.: Key factors involved in pipeline monitoring techniques using robots and WSNs: Comprehensive survey. J. Pipeline Syst. Eng. Pract. 9, 4018001 (2018)

    Article  Google Scholar 

  14. Ivanov, D., Korovin, I., Shabanov, V.: Oil fields monitoring by groups of mobile micro-robots using distributed neural networks. In: 2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), pp. 588–593 (2018)

    Google Scholar 

  15. Casbeer, D.W., Beard, R.W., Mehra, R.K., McLain, T.W.: Forest fire monitoring with multiple small UAVs. In: Proceedings of the 2005, American Control Conference, 2005, pp. 3530–3535. IEEE (2005). https://doi.org/10.1109/ACC.2005.1470520

  16. Tyugin, D.Y., Zeziulin, D. V, Kurkin, A.A., Belyakov, V. V, Makarov, V.S.: Development of a mobile robot group for coastal monitoring. In: IOP Conference Series: Materials Science and Engineering, pp. 12001–12009 (2018

    Google Scholar 

  17. Roldán, J.J., et al.: Robots in agriculture: state of art and practical experiences. Serv. Robot. (2018)

    Google Scholar 

  18. Davoodi, M., Mohammadpour Velni, J., Li, C.: Coverage control with multiple ground robots for precision agriculture. Mech. Eng. 140, S4–S8 (2018)

    Article  Google Scholar 

  19. Vorotnikov, S., Ermishin, K., Nazarova, A., Yuschenko, A.: Multi-agent robotic systems in collaborative robotics. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds.) ICR 2018. LNCS (LNAI), vol. 11097, pp. 270–279. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99582-3_28

    Chapter  Google Scholar 

  20. Gudi, S., Ojha, S., Clark, J., Johnston, B., Williams, M.-A.: Fog robotics: an introduction. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (2017)

    Google Scholar 

  21. Tanwani, A.K., Mor, N., Kubiatowicz, J., Gonzalez, J.E., Goldberg, K.: A fog robotics approach to deep robot learning: application to object recognition and grasp planning in surface decluttering. In: 2019 International Conference on Robotics and Automation (ICRA), pp. 4559–4566 (2019)

    Google Scholar 

  22. Mouradian, C., Naboulsi, D., Yangui, S., Glitho, R.H., Morrow, M.J., Polakos, P.A.: A comprehensive survey on fog computing: State-of-the-art and research challenges. IEEE Commun. Surv. Tutorials. 20, 416–464 (2017)

    Article  Google Scholar 

  23. Gudi, S.L.K.C., Ojha, S., Johnston, B., Clark, J., Williams, M.-A.: Fog robotics for efficient, fluent and robust human-robot interaction. In: 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), pp. 1–5 (2018)

    Google Scholar 

  24. Melnik, E.V., Klimenko, A.B., Ivanov D. Y.: The model of device community forming problem for the geographically-distributed information and control systems using fog-computing concept. In: Proceedings of the IV International Research Conference Information technologies in Science, Management, Social sphere and Medicine, pp. 132–136 (2017)

    Google Scholar 

  25. Korovin, I., Melnik, E., Klimenko, A.: The fog-computing based reliability enhancement in the robot swarm. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds.) ICR 2019. LNCS (LNAI), vol. 11659, pp. 161–169. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-26118-4_16

    Chapter  Google Scholar 

  26. Ivanov, D.: Mobile robots groups use for monitoring and data collection in continuous missions with limited communications. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds.) CoMeSySo 2020. AISC, vol. 1294, pp. 571–581. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-63322-6_46

    Chapter  Google Scholar 

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Acknowledgement

The reported study was funded by RFBR according to the research project № 18-05-80092, № 19-07-00907.

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Authors and Affiliations

  1. Southern Federal University, 2 Chehova St., 3479328, Taganrog, Russia

    Donat Ivanov

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  1. Donat Ivanov
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  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Ivanov, D. (2021). Algorithms for Multi-agent Interaction in the Distribution of Robots in a Group Between Work Areas in Long-Term Monitoring Tasks. In: Silhavy, R. (eds) Informatics and Cybernetics in Intelligent Systems. CSOC 2021. Lecture Notes in Networks and Systems, vol 228. Springer, Cham. https://doi.org/10.1007/978-3-030-77448-6_23

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