1. Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges / B. Chen [et al.] // IEEE Access. - 2018. - No 6. - Pp. 6505 - 6519. -. DOI: 10.1109/ACCESS.2017.2783682 EDN: YEDDHV
2. IEEE Intellectual Property Rights // IEEE - The world’s largest technical professional organization. -IEEE, 2024. - URL: http://www.ieee.org/publications_standards/publications/rights/index.html.
3. Digital twin and virtual reality: a co-simulation environment for design and assessment of industrial workstations/ V. Havard, B. Jeanne, M. Lacomblez, D. Baudry // Production & Manufacturing Research - 2019. - Vol. 7. - No 1. - Pp. 472-489. -. DOI: 10.1080/21693277.2019.1660283
4. A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics / Z. Huang [et al.] // Sensors. - 2021. - Vol. 21. - No 19. - Article 6340. -. DOI: 10.3390/s21196340 EDN: BQBWIS
5. Tyatyushkina O., Ulyanov S.Intelligent cognitive control of robotic sociotechnical systems. Pt.1: Robotic systems and “Human being - robot” interactive models in project “Industry 4.0” // System Analysis in Science and Education. - 2021. - No 3. - Pp. 44-101(In Russ). - URL: http://sanse.ru/download/447. EDN: ZNYELC
6. Ulyanov S. V.Intelligent cognitive control of sociotechnical robotic systems. Pt. 2: Nonlinear model generation of intelligent cognitive robotics for project “Industry 4.0” // System Analysis in Science and Education. - 2021. - No 3. - Pp. 1-43(In Russ). URL: http://sanse.ru/download/449. EDN: WAQUKQ
7. Alcácer V., Cruz-Machado V. Scanning the Industry 4.0: A Literature Review on Technologies for Manufacturing Systems // Intern. J. Eng. Sci. and Technol. - 2019. - Vol. 22. - Pp.899 - 919. -. DOI: 10.1016/j.jestch.2019.01.006
8. Pegman G. Leading European Robotics: Robotic Visions to 2020 and beyond - The Strategic Research Agenda for robotics in Europe. Industrial Technologies Conference Brussels, Belgium, 2020.
9. Intelligent Cognitive Robotics / A. G. Reshetnikov, S. V. Ulyanov, D. P. Zrelova, P. V. Zrelov. - M.: Kurs, 2023. - 464 p. EDN: FOFPAM
10. A Methodology for Flexible Implementation of Collaborative Robots in Smart Manufacturing Systems / H. Giberti [et al.] // Robotics. - 2022. -Vol. 11. - No 9. -. DOI: 10.3390/robotics11010009
11. Intelligent cognitive robotics. Vol. 1: Soft computational intelligence and information-thermodynamic law of intelligent cognitive control / O. Tyatyushkina, A. Reshetnikov, V. Ulyanov [et al.]. - M.: Kurs, 2022. - 528 p. EDN: JMULUL
12. Marinho M. M., Quiroz-Omaña J. J., Harada K. Design and Validation of a Multi-Arm Robot Platform for Scienti c Exploration // arXive.org e-Print archive. - arXiv:2210.11877v1 [cs.RO] 21 Oct 2022.
13. Kaigom E.G. Potentials of the Metaverse for Robotized Applications in Industry 4.0 and Industry 5.0 // arXive.org e-Print archive. - arXiv:2404.00783v1 [cs.RO] 31 Mar 2024.
14. Интеллектуальная когнитивная робототехника. Ч. 1: Технологии квантовых когнитивных вычислений / В. В. Кореньков, С. В. Ульянов, А. А. Шевченко, А. В. Шевченко. - Москва: КУРС, 2022. - 557 с. EDN: ZHQZIT
15. Ulyanov S.V.Intelligent cognitive robotics. Vol. 2. - M.: Kurs, 2022. EDN: JPOUBW
16. Quantum soft engineering toolkit. Pt I. / Ivancova O.V., Korenkov V.V., Ulyanov S.V., Zrelov P.V. - M.: Kurs, 2022.
17. Tyatyushkina O.Yu., Ulyanov S.V. Unmanned Aerial Robotic Vehicles. Pt. 2: Unconventional models of unmanned aerial systems and aerial embedding manipulators // System analysis in science and education. - 2022. - No 3. - Pp. 53-109/ - URL: http://sanse.ru/download/474. EDN: NGSXSA
18. All the Feels: A dexterous hand with large area sensing / R. Bhirangi [et al.] // arXive.org e-Print archive. - arXiv:2210.15658v1 [cs.RO] 27 Oct 2022.
19. Berscheid L., Friedrich C., Kröger T. Robot Learning of 6DoF Grasping using Model-based Adaptive Primitives // arXive.org e-Print archive. - arXiv:2103.12810v1 [cs.RO] 23 Mar 2021.
20. Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi- uid Objects /j. Liu [et al.] // arXive.org e-Print archive. - arXiv:2205.05960v1 [cs.RO] 12 May 2022.
21. SAM-RL: Sensing-Aware Model-Based Reinforcement Learning via Differentiable Physics-Based Simulation and Rendering / Jun Lv [et al.] // arXive.org e-Print archive. - arXiv:2210.15185v1 [cs.RO] 27 Oct 2022.
22. Robust Control of a New Asymmetric Teleoperation Robot Based on a State Observer / B. Shi, H. Wu, Y. Zhu, M. Shang, // Sensors. - 2021. - Vol. 21. - Pp. 6197. DOI: 10.3390/s21186197 EDN: AYPQBF
23. Caveats on the rst-generation da Vinci Research Kit: latent technical constraints and essential calibrations / Z. Cui, J. Cartucho, S. Giannarou, F. R. y Baena // arXive.org e-Print archive. - arXiv:2210.13598v1 [cs.RO] 24 Oct 2022.
24. Kasaei H., Kasaei M. Throwing Objects into A Moving Basket While Avoiding Obstacles // arXive.org e-Print archive. - arXiv:2210.00609v1 [cs.RO] 2 Oct 2022.
25. A Mixed-Reality Tele-Operation Method for High-Level Control of a Legged-Manipulator Robot / C. Cruz Ulloa, D. Domínguez, J. Del Cerro, A. Barrientos // Sensors. - 2022. - Vol. 22. - No 21. - Pp. 8146. -. DOI: 10.3390/s22218146 EDN: HYJQBM
26. Towards Semantic Integration of Machine Vision Systems to Aid Manufacturing Event Understanding / K. Xia [et al.] // Sensors. - 2021. - Vol. 21. - No 13. - Pp. 4276. -. DOI: 10.3390/s21134276 EDN: DPKPDJ
27. Multimodal Human-Robot Interface for Accessible Remote Robotic Interventions in Hazardous Environments / G. Lunghi [et al.] // IEEE Access. - 2019. - Vol. 7. - Pp. 127290 - 127319. -. DOI: 10.1109/ACCESS.2019.293949
28. Sheridan T. B. Human-Robot Interaction: Status and Challenges // Human factors. - 2016. - Vol. 58. - No. 4. - Pp. 525 -532. -. DOI: 10.1177/0018720816644364
29. MiniCERNBot Educational Platform: Antimatter Factory Mock-up Missions for Problem-Solving STEM Learning / M. Garcés [et al.] // Sensors. - 2021. - Vol. 21. - Pp. 1398. -. DOI: 10.3390/s21041398 EDN: WLXEBW
30. Tyatyushkina O.Yu., Ulyanov S.V. Unmanned Aerial Vehicles. Pt. 1: Bio-inspired and aerial-aquatic locomotion // System analysis in science and education. - 2022. - No 3. - Pp. 8-52. - URL: http://sanse.ru/download/473. EDN: THYHHT
31. Tyatyushkina O.Yu., Ulyanov S.V. Unmanned Aerial Robotic Vehicles. Pt. 2: Unconventional models of unmanned aerial systems and aerial embedding manipulators // System analysis in science and education. - 2022. - No 3. - Pp. 53-109. - URL: http://sanse.ru/download/474. EDN: NGSXSA
32. Mohiuddin A. et al. A survey of single and multi-UAV aerial manipulation // Unmanned Systems. - 2020. - Vol. 8. - No 2. - Pp. 119-147. -. DOI: 10.1142/S2301385020500089 EDN: RSXXBE
33. Past, Present and Future of Aerial Robotic Manipulators / A. Ollero [et al.] // IEEE TRANSACTIONS ON ROBOTICS. - 2022. - Vol. 38. - No. 1. - Pp. 626-645. - [Preprint version nal version at http://ieeexplore.ieee.org/, 2021.]. EDN: BWUDGN
34. Sanalitro D. Aerial Cooperative Manipulation: full pose manipulation in air and in interaction with the environment. - DOCTORAT DE L’UNIVERSITÉ FÉDÉRALE TOULOUSE MIDI-PYRÉNÉES. l’Institut National des Sciences Appliquées de Toulouse (INSA de Toulouse), 2022.
35. Huan N., Kostas A. Forceful Aerial Manipulation based on an Aerial Robotic Chain: Hybrid Modeling and Control // IEEE Robotics and Automation Letters. - 2021. - Vol. 6. - No 2. - Pp. 3711-3719. -. DOI: 10.1109/LRA.2021.3064254 EDN: DFBASM
36. Zhao M., Anzai T., Nishio T. Design, Modeling and Control of a Quadruped Robot SPIDAR: Spherically Vectorable and Distributed Rotors Assisted Air-Ground Amphibious Quadruped Robot // arXive.org e-Print archive. - arXiv:2301.04050v1 [cs.RO] 10 Jan 2023.
37. The current state and future outlook of rescue robotics / Delmerico J. et al. // Journal of Field Robotics. - 2019. -Pp. 1-21. -. DOI: 10.1002/rob.21887
38. A survey of quantum computing hybrid applications with brain-computer interface / D. Huang, M. Wang, J. Wang, J. Yan // Cognitive Robotics. - 2022. - Vol. 2. - Pp. 164-176. -. DOI: 10.1016/j.cogr.2022.07.002 EDN: RCVPLY
39. Hybrid EEG-EMG based brain computer interface (BCI) system for real-time robotic arm control / S. Abdullah, M. A. Khan, M. Serpelloni, E. Sardini // Advanced Materials Letters. - 2019. - Vol. 10. - No 1. - Pp. 35-40. -. DOI: 10.5185/amlett.2019.2171
40. Duarte R. M. Low cost Brain Computer Interface system for AR Drone Control. - PhD Thesis. UNIVERSIDADE FEDERAL DE SANTA CATARINA CENTRO TECNOLÓGICO PROGRAMA DE PÓS GRADUAÇÃO EM ENGENHARIA DE AUTOMAÇÃO E SISTEMAS, 2017.
41. van Erp T., Gladysz B. Quantum Technologies in Manufacturing Systems: Perspectives for Application and Sustainable Development // Procedia CIRP. - 2022. - Vol. 107. - Pp.1120-1125. -. DOI: 10.1016/j.procir.2022.05.118 EDN: MYMWIC
42. Artificial Intelligence and Machine Learning for Quantum Technologies / M. Krenn, J. Landgraf, T. Foesel, F. Marquardt // arXive.org e-Print archive. - arXiv:2208.03836v1 [quant-ph] 7 Aug 2022.
43. Industry quantum computing applications / A. Bayerstadler [et al.] // EPJ Quantum Technology. - 2021. - Vol. 8. - Article number: 25 (2021). -. DOI: 10.1140/epjqt/s40507-021-00114-x
44. Quantum Communication Systems: Vision, Protocols, Applications, and Challenges /Syed Rakib Hasan, Mostafa Zaman Chowdhury, Md. Saiam, Yeong Min Jang // arXive.org e-Print archive. - arXiv: 2212.13333v1 [quant-ph] 29 Dec 2022.
45. Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future / S. J. Nawaz [et al.] // IEEE Access. - Vol.7. - Pp. 46317-46350. -. DOI: 10.1109/ACCESS.2019.2909490