Ensuring scalability and specified fault tolerance level of robots control systems

DOI: 10.34759/trd-2020-111-19


Romanov A. M.

MIREA - Russian Technological University, 78, Vernadsky prospect, Moscow, 119454, Russia

e-mail: romanov@mirea.ru


The article studies the issue of scalability and fault tolerance ensuring of robot control systems. Based on the analysis of the existing approaches in robotics, a set of techniques is proposed for ensuring the required fault tolerance level, as well as a control system scaling model based on them, which allows employing unified design principles for robots of various sizes and purposes. Creating and scaling robots according to this model allows maximal employing of all previously obtained results, and accelerating creation of the new market-ready products and their upgrade in the future. The model simplifies significantly conversion between various robotics areas including industrial, mobile, aerospace etc. In the course of the conceptual model description the author formulates further trends of research necessary for its realization. The suggested concept fully serves the Industry 4.0 ideology, when specialization of each product with preserving the fast time of its market entry rather than the possibilities of mass serial production, even customized, comes to the foreground.


robotics, fault tolerance, scalability, component base, control system


  1. Romanov A.M. Rossiiskii tekhnologicheskii zhurnal, 2019, vol. 7, no. 5, pp. 30 - 46.

  2. Romanov A.M. Rossiiskii tekhnologicheskii zhurnal, 2019, vol. 7, no 6, pp. 68 - 86.

  3. Wang Y. et al. Industry 4.0: a way from mass customization to mass personalization production, Advances in Manufacturing, 2017, vol. 5, no. 4, pp. 311 - 320. DOI: 10.1007/s40436-017-0204-7

  4. Mikhailova E.A., Kamakina O.V., Efimova P.E. Trudy MAI, 2014, no. 77, available at: http://trudymai.ru/eng/published.php?ID=53191

  5. Funktsional'naya bezopasnost' elektricheskikh/elektronnykh/programmiruemykh elektronnykh sistem bezopasnosti. GOST R MEK 61508 (Functional safety of electrical/electronic/programmable electronic safety-related systems IEC 61508), Moscow, Standartinform, 2010, 204 p.

  6. International Electrotechnical Commission et al. IEC 62061, Safety of machinery-Functional safety of safety-related electrical, electronic and programmable electronic control systems, IEC Standards Online, 2005.

  7. Hegde V. Reliability in the medical device industry. Handbook of Performability Engineering, Springer, London, 2008, pp. 997 - 1009.

  8. Obukhov Yu.V., Popov A.S., Orlov A.S., Kotova A.O. Trudy MAI, 2015, no. 81, available at: http://trudymai.ru/eng/published.php?ID=57729

  9. Gur'yanov A.V. et al. Izvestiya Samarskogo nauchnogo tsentra Rossiiskoi akademii nauk, 2017, vol. 19, no. 1-2, pp. 341 - 345.

  10. Yurkov N.K., Trusov V.A., Lysenko A.V. XIII Mezhdunarodnaya nauchno-tekhnicheskaya konferentsiya “Aktual'nye problemy elektronnogo priborostroeniya”, Novosibirsk, Novosibirskii gosudarstvennyi tekhnicheskii universitet, 2016, pp. 134 - 138.

  11. Qin J. et al. Reliability analysis of avionics in the commercial aerospace industry, Journal of the Reliability Analysis Center, 2005, pp. 1 - 6.

  12. McLeish J. et al. SAE J3168: A Joint Aerospace-Automotive Recommended Practice for Reliability Physics Analysis of Electrical, Electronic and Electromechanical Components, SAE Technical Paper № 2019-01-1252, 2019, DOI: https://doi.org/10.4271/2019-01-1252

  13. Cavallaro J., Walker I. A survey of NASA and military standards on fault tolerance and reliability applied to robotics, Conference on Intelligent Robots in Factory, Field, Space and Service, 1994, 1211 p. https://doi.org/10.2514/6.1994-1211

  14. Sizova K.G., Skorobogatov P.K., Prygunov M.O. Bezopasnost' informatsionnykh tekhnologii, 2018, vol. 25, no. 1, pp. 52 - 64.

  15. Alchinov V.I., Sidorov A.I., Chistova G.K. Nadezhnost' tekhnicheskikh sistem voennogo naznacheniya (Reliability of military-grade technical systems: a tutorial), Moscow – Vologda, Infra-Inzheneriya, 2019, vol.1, 324 p.

  16. Khobare S.K. et al. Reliability analysis of microcomputer circuit modules and computer based control systems important to safety of nuclear power plants, Reliability Engineering & System Safety, 1998, vol. 59, no. 2, pp. 253 - 258.

  17. Zharko E.F. Informatsionnye tekhnologii i vychislitel'nye sistemy, 2011, no. 3, pp. 38 - 44.

  18. Lakner A.A., Anderson R.T. Reliability Engineering for Nuclear and Other High Technology Systems (1985): A practical guide, CRC Press, 2017, 440 p.

  19. Walker I.D., Cavallaro J.R. Failure mode analysis for a hazardous waste clean-up manipulator, Reliability Engineering & System Safety, 1996, vol. 53, no. 3, pp. 277 - 290.

  20. Dhillon B.S. Robot reliability and safety, Springer Science & Business Media, 2012, 254 p.

  21. Gracie E., Hayek A., Börcsök J. Evaluation of FPGA design tools for safety systems with on-chip redundancy referring to the standard IEC 61508, 2017 2nd International Conference on System Reliability and Safety (ICSRS), IEEE, 2017, pp. 386 - 390. DOI: 10.1109/ICSRS.2017.8272853

  22. Romanov A.M. Trudy MAI, 2019, no 106, available at: http://trudymai.ru/eng/published.php?ID=105741

  23. Zavedeev A.I. Trudy MAI, 2012, no. 54, available at: http://trudymai.ru/eng/published.php?ID=29687

  24. Zavedeev A.I., Kovalev A.Yu. Trudy MAI, 2012, no. 54, available at: http://trudymai.ru/eng/published.php?ID=29688

  25. Grebenyuk V.M. Naukovedenie, 2013, no. 3 (16), available at: https://naukovedenie.ru/index.php?p=issue-3-13-technics

  26. Mahmood A. et al. Clock synchronization over IEEE 802.11—A survey of methodologies and protocols, IEEE Transactions on Industrial Informatics, 2017, vol. 13, no. 2, pp. 907 - 922. DOI:10.1109/TII.2016.2629669

  27. Wang W., Siau K. Artificial Intelligence, Machine Learning, Automation, Robotics, Future of Work and Future of Humanity: A Review and Research Agenda, Journal of Database Management (JDM), 2019, vol. 30, no. 1, pp. 61 - 79. DOI: 10.4018/JDM.2019010104

  28. Pierson H.A., Gashler M.S. Deep learning in robotics: a review of recent research, Advanced Robotics, 2017, vol. 31, no. 16, pp. 821 - 835. DOI:10.1080/01691864.2017.1365009

  29. Wan J. et al. Cloud robotics: Current status and open issues, IEEE Access, 2016, vol. 4, pp. 2797 - 2807. DOI: 10.1109/ACCESS.2016.2574979

  30. Duggan L. et al. A rapid deployment big data computing platform for cloud robotics, International Journal of Computer Networks and Communications, 2017, pp. 9, no. 6. pp. 77 - 88. DOI: 10.5121/ijcnc.2017.9606

  31. Bianchi R.A.C. et al. Heuristically accelerated reinforcement learning by means of case-based reasoning and transfer learning, Journal of Intelligent & Robotic Systems, 2018, vol. 91, no. 2, pp. 301 - 312.

  32. Shahapure N.H., Jayarekha P. Virtual machine migration based load balancing for resource management and scalability in cloud environment, International Journal of Information Technology, 2018, pp. 1 -1 2. DOI: 10.1007/s41870-018-0216-y

  33. Chen W. et al. A study of robotic cooperation in cloud robotics: Architecture and challenges, IEEE Access, 2018, vol. 6, pp. 36662 - 36682. DOI:10.1109/ACCESS.2018.2852295

  34. Bogue R. Cloud robotics: a review of technologies, developments and applications, Journal Industrial Robot, 2017, vol. 44, no. 1, pp. 1 - 5. DOI: 10.1108/IR-10-2016-0265

  35. Gupta R. et al. Tactile internet and its applications in 5G era: A comprehensive review, International Journal of Communication Systems, 2019, vol. 32, no. 14. DOI: 10.1002/dac.3981

  36. Sanchez D. O. M. Corporate Social Responsibility Challenges and Risks of Industry 4.0 technologies: A review, Smart SysTech 2019; European Conference on Smart Objects, Systems and Technologies, VDE, 2019, pp. 1 - 8.

  37. Dorigo M. et al. Blockchain Technology for Robot Swarms: A Shared Knowledge and Reputation Management System for Collective Estimation, Swarm Intelligence: 11th International Conference, ANTS 2018, Rome, Italy, October 29–31, 2018, Proceedings, Springer, 2018, vol. 11172, pp. 425.

  38. Ferrer E.C. The blockchain: a new framework for robotic swarm systems, Proceedings of the Future Technologies Conference, Springer, Cham, 2018, pp. 1037 - 1058. DOI:10.1007/978-3-030-02683-7_77

  39. Nguyen T.T., Hatua A., Sung A.H. Blockchain Approach to Solve Collective Decision Making Problems for Swarm Robotics, International Congress on Blockchain and Applications, Springer, Cham, 2019, pp. 118 - 125. DOI: 10.1007/978-3-030-23813-1_15

  40. Maxfield C. The design warrior's guide to FPGAs: devices, tools and flows, Elsevier, 2004, 542 p.


mai.ru — informational site MAI

Copyright © 2000-2022 by MAI