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Intelligent Robots Coalition Formation in Cyberphysical Space for Emergency Response

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Cyber-Physical Systems: Modelling and Intelligent Control

Abstract

Coalitions of robots equipped with a set of special sensors and actuators can be used for rescuing injured people in emergency situations. These sets will vary depending on the type of emergency and the activity of the environment, which, in turn, also affects the options for the interaction of robots and their tasks. In this chapter, the use of cyber-physical systems concept is proposed to form a common information-physical space in which robots will perform joint actions for eliminating the consequences of an emergency. Each robot in the coalition takes into account the specific of the emergency and the developing situation at the emergency site. Robots consider parameters of developing situations through their ontological description. The total functionality of the coalition covers the requirements of the tasks. Monitoring a developing situation allows making a timely decision on changing the composition of the coalition if the conditions change in such a way that the current composition becomes ineffective. The interaction of robots and the implementation of the rules for changing the coalition is carried out through smart contracts in a distributed ledger. This provides the opportunity to control the actions of the coalition and reduce the likelihood of being incorporated into the coalition in order to disrupt the coherence of the actions of its individual members.

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References

  1. Fisher, D. (IFRC), Hagon, K. (IFRC), Lattimer, C., O’Callaghan, S., Swithern, S., Walmsley, L.: World Disasters Report 2018. In: Leaving No One Behind: The International Humanitarian Sector Must Do More to Respond to the Needs of the World’s Most Vulnerable People (2018)

    Google Scholar 

  2. Tadokoro, S., Kimura, T., Okugawa, M., Oogane, K., Igarashi, H., Ohtsubo, Y., Sato, N., Shimizu, M., Suzuki, S., Takahashi, T., Nakaoka, S., Murata, M., Takahashi, M., Morita, Y., Rooney, E.M.: The World robot summit disaster robotics category–achievements of the 2018 preliminary competition. Adv. Robot. 33, 854–875 (2019). https://doi.org/10.1080/01691864.2019.1627244

    Article  Google Scholar 

  3. Korzun, D., Kashevnik, A., Balandin, S.: Novel design and the applications of smart-M3 platform in the internet of things. IGI Global (2018). https://doi.org/10.4018/978-1-5225-2653-7

  4. Guerrero, J., Oliver, G.: Multi-robot coalition formation in real-time scenarios. Robot. Auton. Syst. 60, 1295–1307 (2012). https://doi.org/10.1016/j.robot.2012.06.004

    Article  Google Scholar 

  5. Mareš, M.: In: Fuzzy Cooperative Games. Physica-Verlag HD, Heidelberg (2001). https://doi.org/10.1007/978-3-7908-1820-8

  6. Cong, L.W., He, Z., Zheng, J.: Blockchain disruption and smart contracts. SSRN Electron. J. 48 (2017). https://doi.org/10.2139/ssrn.2985764

  7. Delmolino, K., Arnett, M., Kosba, A., Miller, A., Shi, E.: Step by step towards creating a safe smart contract: lessons and insights from a cryptocurrency lab. In: Grossklags, J., Preneel, B. (eds.) Financial Cryptography and Data Security. FC 2016. pp. 79–94. Springer, Berlin, Heidelberg (2016). https://doi.org/10.1007/978-3-662-53357-4_6

  8. Armbrust, C., De Cubber, G., Berns, K.: ICARUS Control systems for search and rescue robots. In: Field and Assistive Robotics–Advances in Systems and Algorithms. pp. 1–16 (2014)

    Google Scholar 

  9. Levinger, J., Hofmann, A., Theobald, D.: Semi-autonomous control of an emergency response robot. AUVSI Unmanned Syst. North Amer. Conf. 2008(2), 914–927 (2008)

    Google Scholar 

  10. Robot| Mini Robocue| Robotics Today. https://www.roboticstoday.com/robots/mini-robocue. Last Accessed 09 Jul 2020

  11. Bogdanov, A., Dudorov, E., Permyakov, A., Pronin, A., Kutlubaev, I.: Control system of a manipulator of the anthropomorphic robot fedor. In: Proceedings-International Conference on Developments in eSystems Engineering, DeSE. pp. 449–453. Institute of Electrical and Electronics Engineers Inc. (2019). https://doi.org/10.1109/DeSE.2019.00088

  12. Haynes, G.C., Stager, D., Stentz, A., Vande Weghe, J.M., Zajac, B., Herman, H., Kelly, A., Meyhofer, E., Anderson, D., Bennington, D., Brindza, J., Butterworth, D., Dellin, C., George, M., Gonzalez-Mora, J., Jones, M., Kini, P., Laverne, M., Letwin, N., Perko, E., Pinkston, C., Rice, D., Scheifflee, J., Strabala, K., Waldbaum, M., Warner, R.: Developing a robust disaster response robot: CHIMP and the robotics challenge. J. Field Robot. 34, 281–304 (2017). https://doi.org/10.1002/rob.21696

    Article  Google Scholar 

  13. Park, I.W., Kim, J.Y., Lee, J., Oh, J.H.: Mechanical design of humanoid robot platform KHR-3 (KAIST humanoid robot-3: HUBO). In: Proceedings of 2005 5th IEEE-RAS International Conference on Humanoid Robots. pp. 321–326 (2005). https://doi.org/10.1109/ICHR.2005.1573587

  14. Feng, S., Whitman, E., Xinjilefu, X., Atkeson, C.G.: Optimization based full body control for the atlas robot. In: IEEE-RAS International Conference on Humanoid Robots. pp. 120–127. IEEE Computer Society (2015). https://doi.org/10.1109/HUMANOIDS.2014.7041347

  15. Smirnov, A., Kashevnik, A., Ponomarev, A.: Multi-level self-organization in cyber-physical-social systems: Smart home cleaning scenario. In: Procedia CIRP. pp. 329–334. Elsevier B.V. (2015). https://doi.org/10.1016/j.procir.2015.02.089

  16. Verma, D., Desai, N., Preece, A., Taylor, I.: A block chain based architecture for asset management in coalition operations. In: Pham, T., Kolodny, M.A. (eds.) Proceedings SPIE 10190, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VIII. pp. 101900Y (2017). https://doi.org/10.1117/12.2264911

  17. Dorri, A., Kanhere, S.S., Jurdak, R.: Towards an optimized blockchain for IoT. In: Proceedings of the Second International Conference on Internet-of-Things Design and Implementation-IoTDI’17. pp. 173–178. (2017). https://doi.org/10.1145/3054977.3055003

  18. Zhang, Y., Wen, J.: The IoT electric business model: using blockchain technology for the internet of things. Peer-to-Peer Netw. Appl. 10, 983–994 (2017). https://doi.org/10.1007/s12083-016-0456-1

    Article  Google Scholar 

  19. Ferrer, E.C.: The blockchain: a new framework for robotic swarm systems. Adv. Intell. Syst. Comput. 881, 1037–1058 (2019). https://doi.org/10.1007/978-3-030-02683-7_77

    Article  Google Scholar 

  20. Smirnov, A., Sheremetov, L., Teslya, N.: Fuzzy cooperative games usage in smart contracts for dynamic robot coalition formation: approach and use case description. In: ICEIS 2019-Proceedings of the 21st International Conference on Enterprise Information Systems. pp. 349–358. SCITEPRESS-Science and Technology Publications (2019). https://doi.org/10.5220/0007763003610370

  21. IEEE Robotics and Automation Society: In: IEEE Standard Ontologies for Robotics and Automation (2015). https://doi.org/10.1109/IEEESTD.2015.7084073

  22. Haekwan, L., Tanaka, H.: Fuzzy approximations with non-symmetric fuzzy parameters in fuzzy regression analysis. J. Oper. Res. Soc. Japan 42, 98–112 (1999)

    MathSciNet  MATH  Google Scholar 

  23. Zadeh, L.A.: Similarity relations and fuzzy orderings. Inf. Sci. 3, 177–200 (1971). https://doi.org/10.1016/S0020-0255(71)80005-1

    Article  MathSciNet  MATH  Google Scholar 

  24. Smirnov, A., Sheremetov, L., Teslya, N.: Fuzzy cooperative games usage in smart contracts for dynamic robot coalition formation: Approach and use case description. In: ICEIS 2019-Proceedings of the 21st International Conference on Enterprise Information Systems. pp. 349–358 (2019)

    Google Scholar 

  25. Teslya, N.: Industrial socio-cyberphysical system’s consumables tokenization for smart contracts in blockchain. In: Lecture Notes in Business Information Processing. pp. 344–355. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-04849-5_31

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Acknowledgements

The present research was supported by the Russian Foundation for Basic Research, project number 17-29-07073 in the field of dynamic coalition formation for emergency medicine, and by Russian State Research No. 0073-2019-0005 for creating a cyberphysical space for intelligent robot interaction.

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Smirnov, A., Teslya, N., Motienko, A. (2021). Intelligent Robots Coalition Formation in Cyberphysical Space for Emergency Response. In: Kravets, A.G., Bolshakov, A.A., Shcherbakov, M. (eds) Cyber-Physical Systems: Modelling and Intelligent Control. Studies in Systems, Decision and Control, vol 338. Springer, Cham. https://doi.org/10.1007/978-3-030-66077-2_22

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  • DOI: https://doi.org/10.1007/978-3-030-66077-2_22

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