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Distributing Tasks in Multi-agent Robotic System for Human-Robot Interaction Applications

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Interactive Collaborative Robotics (ICR 2020)

Abstract

Human-robot interaction become a trend in robotics and happen in a wide range of situations. This research paper describes human and collaborative robots interaction behind traditional paradigms for robots in a shared workspace. This research shows that humans and robots distributing task in collaborative interaction of multi-agent robotic system. Different methods for distributing tasks on global and local levels in multi-agent robotic system analyzed as part of research work. Characteristics of tasks distribution algorithms are considered. The particle swarm algorithm for task distribution presented as an example.

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References

  1. Ermishin, K., Yuschenko, A: Collaborative mobile robots - a new stage of development of service robotics. J. Robot. Tech. Cybern. 3(12), 3–9 (2016)

    Google Scholar 

  2. Matheson, E.: Human-robot collaboration in manufacturing applications: a review. Robotics 8(4), 100 (2019). https://doi.org/10.3390/robotics8040100

    Article  Google Scholar 

  3. Galin, R., Meshcheryakov, R.: Review on human–robot interaction during collaboration in a shared workspace. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds.) ICR 2019. LNCS (LNAI), vol. 11659, pp. 63–74. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-26118-4_7

    Chapter  Google Scholar 

  4. Villani, V., Pini, F., Leali, F., Secchi, C.: Survey on human–robot collaboration in industrial settings: safety, intuitive interfaces and applications. Mechatronics 55, 248–266 (2018). https://doi.org/10.1016/j.mechatronics.2018.02.009

    Article  Google Scholar 

  5. ISO 10218-1, 2:2011: Robots and robotic devices – Safety requirements for industrial robots – Part 1, 2: Robot systems and integration, Geneva (2011)

    Google Scholar 

  6. ISO: 12100:2010–11 Safety of machinery - General principles for design – Risk assessment and risk reduction. Standard, International Organization for Standardization (2013)

    Google Scholar 

  7. ISO/TC 299 Robotics – “ISO/TS 15066:2016 Robots and robotic devices – Collaborative robots”. https://www.iso.org/standard/62996.html. Accessed 11 May 2020

  8. Lazarte, M.: Robots and humans can work together with new ISO guidance. https://www.iso.org/news/2016/03/Ref2057.html. Accessed 13 May 2020

  9. Galin, R.R., Meshcheryakov, R.V.: Human-robot interaction efficiency and human-robot collaboration. In: Kravets, A. (ed.) Robotics: Industry 4.0 Issues & New Intelligent Control Paradigms. SSDC, vol. 272, pp. 55–63. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-37841-7_5

    Chapter  Google Scholar 

  10. Kaiser, L., Schlotzhauer, A., Brandstötter, M.: Safety-related risks and opportunities of key design-aspects for industrial human-robot collaboration. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds.) ICR 2018. LNCS (LNAI), vol. 11097, pp. 95–104. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99582-3_11

    Chapter  Google Scholar 

  11. 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 

  12. Magrini, E., et al.: Human-robot coexistence and interaction in open industrial cells. Robot. Comput.-Integr. Manuf. 61, 101846 (2020). https://doi.org/10.1016/j.rcim.2019.101846

    Article  Google Scholar 

  13. Schmidtler, J., Knott, V., Hölzel, C., Bengler, K.: Human centered assistance applications for the working environment of the future. Occup. Ergon. 12(3), 83–95 (2015)

    Article  Google Scholar 

  14. Hoffman, G.: Evaluating fluency in human–robot collaboration. IEEE Trans. Hum.-Mach. Syst. 1–10 (2019). https://doi.org/10.1109/thms.2019.2904558

  15. Lin, F., Hsu, J.Y.: Cooperation protocols in multi-agent robotic systems. Auton. Robots 4, 175–198 (1997). https://doi.org/10.1023/a:1008813631823

    Article  Google Scholar 

  16. Charalambous, G., et al.: Human-automation collaboration in manufacturing: identifying key implementation factors. In: ICMR 2013, pp. 301–306. Cranfield University, UK (2013)

    Google Scholar 

  17. Galin, R., et al.: Cobots and the benefits of their implementation in intelligent manufacturing. IOP Conf. Ser.: Mater. Sci. Eng. 862, 032075 (2020). https://doi.org/10.1088/1757-899x/862/3/032075

  18. Nazarova, A.V., Zhai, M.: Distributed solution of problems in multi agent robotic systems. In: Gorodetskiy, A.E., Tarasova, I.L. (eds.) Smart Electromechanical Systems. SSDC, vol. 174, pp. 107–124. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-99759-9_9

    Chapter  Google Scholar 

  19. Liu, C., Tomizuka, M.: Designing the robot behavior for safe human–robot interactions. In: Wang, Y., Zhang, F. (eds.) Trends in Control and Decision-Making for Human–Robot Collaboration Systems. SSDC, pp. 241–270. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-40533-9_11

    Chapter  Google Scholar 

  20. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural Networks, pp. 1942–1948 (1995)

    Google Scholar 

  21. Wang, Y., Zeng, J.: A survey of a multi-objective particle swarm optimization algorithm. CAAI Trans. Intell. Syst. 5(5), 377–384 (2010)

    Google Scholar 

  22. Azzouz, R., Bechikh, S., Ben Said, L.: Dynamic multi-objective optimization using evolutionary algorithms: a survey. In: Bechikh, S., Datta, R., Gupta, A. (eds.) Recent Advances in Evolutionary Multi-objective Optimization. ALO, vol. 20, pp. 31–70. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-42978-6_2

    Chapter  Google Scholar 

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Acknowledgements

The reported study was partially funded by RFBR according to the research project № 19-08-00331.

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Correspondence to Rinat Galin .

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Galin, R., Meshcheryakov, R., Kamesheva, S. (2020). Distributing Tasks in Multi-agent Robotic System for Human-Robot Interaction Applications. In: Ronzhin, A., Rigoll, G., Meshcheryakov, R. (eds) Interactive Collaborative Robotics. ICR 2020. Lecture Notes in Computer Science(), vol 12336. Springer, Cham. https://doi.org/10.1007/978-3-030-60337-3_10

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  • DOI: https://doi.org/10.1007/978-3-030-60337-3_10

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  • Online ISBN: 978-3-030-60337-3

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