Research of Existing Methods of Representing a Collaborative Robot-Manipulator Environment within the Framework of Cyber-Physical Production Systems

Vladyslav Yevsieiev; Ahmad Alkhalaileh; Svitlana Maksymova; Dmytro Gurin

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Published

2024-09-23

Issue

Vol. 4 No. 9 (2024): Multidisciplinary Journal of Science and Technology

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Articles

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Research of Existing Methods of Representing a Collaborative Robot-Manipulator Environment within the Framework of Cyber-Physical Production Systems. (2024). Multidisciplinary Journal of Science and Technology, 4(9), 112-120. http://mjstjournal.com/index.php/mjst/article/view/1855

How to Cite

Research of Existing Methods of Representing a Collaborative Robot-Manipulator Environment within the Framework of Cyber-Physical Production Systems. (2024). Multidisciplinary Journal of Science and Technology, 4(9), 112-120. http://mjstjournal.com/index.php/mjst/article/view/1855

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Research of Existing Methods of Representing a Collaborative Robot-Manipulator Environment within the Framework of Cyber-Physical Production Systems

Vladyslav Yevsieiev

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Ahmad Alkhalaileh

Senior Developer Electronic Health Solution, Amman, Jordan

Svitlana Maksymova

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Dmytro Gurin

Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Keywords: Industry 5.0, Collaborative Robot, Work Area, Computer Vision, Robot-Manipulator.

Abstract

The article is devoted to the research of existing methods of representing a collaborative robot-manipulator environment in the context of cyber-physical production systems. The advantages and limitations of various approaches are analyzed, in particular their suitability for dynamic information updating and integration with robotic systems. The results of the study emphasize the importance of choosing appropriate methods to ensure effective interaction between humans and robots, which is relevant within the concept of Industry 5.0.

References

1. Abu-Jassar, A., & et al. (2023). Obstacle Avoidance Sensors: A Brief Overview. Multidisciplinary Journal of Science and Technology, 3(5), 4-10.

2. Maksymova, S., & et al. (2024). The Lucas-Kanade method implementation for estimating the objects movement in the mobile robot’s workspace. Journal of Universal Science Research, 2(3), 187-197.

3. Akopov, M., & et al. (2023). Choosing a Camera for 3D Mapping. Journal of Universal Science Research, 1(11), 28–38.

4. Maksymova, S., & et al. (2023). Selection of Sensors for Building a 3D Model of the Mobile Robot's Environment. In Manufacturing & Mechatronic Systems 2023: Proceedings of VII International Conference, Kharkiv, 33-35.

5. Yevsieiev, V., & et al. (2024). Building a traffic route taking into account obstacles based on the A-star algorithm using the python language. Technical Science Research In Uzbekistan, 2(3), 103-112.

6. Samoilenko, H., & et al. (2024). Review for Collective Problem-Solving by a Group of Robots. Journal of Universal Science Research, 2(6), 7-16.

7. Nevliudov, I., Yevsieiev, V., Baker, J. H., Ahmad, M. A., & Lyashenko, V. (2020). Development of a cyber design modeling declarative Language for cyber physical production systems. J. Math. Comput. Sci., 11(1), 520-542.

8. Sotnik, S., Mustafa, S. K., Ahmad, M. A., Lyashenko, V., & Zeleniy, O. (2020). Some features of route planning as the basis in a mobile robot. International Journal of Emerging Trends in Engineering Research, 8(5), 2074-2079.

9. Nevliudov, I., & et al.. (2020). Method of Algorithms for CyberPhysical Production Systems Functioning Synthesis. International Journal of Emerging Trends in Engineering Research, 8(10), 7465-7473.

10. Mustafa, S. K., Yevsieiev, V., Nevliudov, I., & Lyashenko, V. (2022). HMI Development Automation with GUI Elements for Object-Oriented Programming Languages Implementation. SSRG International Journal of Engineering Trends and Technology, 70(1), 139-145.

11. Matarneh, R., Tvoroshenko, I., & Lyashenko, V. (2019). Improving Fuzzy Network Models For the Analysis of Dynamic Interacting Processes in the State Space. International Journal of Recent Technology and Engineering, 8(4), 1687-1693.

12. Lyashenko, V., Abu-Jassar, A. T., Yevsieiev, V., & Maksymova, S. (2023). Automated Monitoring and Visualization System in Production. International Research Journal of Multidisciplinary Technovation, 5(6), 9-18.

13. Abu-Jassar, A. T., Attar, H., Lyashenko, V., Amer, A., Sotnik, S., & Solyman, A. (2023). Access control to robotic systems based on biometric: the generalized model and its practical implementation. International Journal of Intelligent Engineering and Systems, 16(5), 313-328.

14. Al-Sharo, Y. M., Abu-Jassar, A. T., Sotnik, S., & Lyashenko, V. (2023). Generalized Procedure for Determining the Collision-Free Trajectory for a Robotic Arm. Tikrit Journal of Engineering Sciences, 30(2), 142-151.

15. Невлюдов, І. Ш., & et al. (2023). Моделі та методи кіберфізичних виробничих систем в концепції Industry 4.0. Prague, Oktan Print, 321.

16. Євсєєв, В. В., & Максимова, С. С. (2020). Технологія процесу керування розробкою кіберфізичних виробничих систем. Вчені записки, 5202057.

17. Nevliudov, I., & et al. (2020). Development of an architecturallogical model to automate the management of the process of creating complex cyberphysical industrial systems. Восточно-Европейский журнал передовых технологий, 4(3-106), 44-52.

18. Ahmad, M. A., Sinelnikova, T., Lyashenko, V., & Mustafa, S. K. (2020). Features of the construction and control of the navigation system of a mobile robot. International Journal of Emerging Trends in Engineering Research, 8(4), 1445-1449.

19. Lyashenko, V., Laariedh, F., Ayaz, A. M., & Sotnik, S. (2021). Recognition of Voice Commands Based on Neural Network. TEM Journal: Technology, Education, Management, Informatics, 10(2), 583-591.

20. Lyashenko, V., & et al.. (2021). Semantic Model Workspace Industrial Robot. International Journal of Academic Engineering Research, 5(9), 40-48.

21. Sotnik, S., & et al.. (2022). Analysis of Existing Infliences in Formation of Mobile Robots Trajectory. International Journal of Academic Information Systems Research, 6(1), 13-20.

22. Sotnik, S., & et al.. (2022). Modern Industrial Robotics Industry. International Journal of Academic Engineering Research, 6(1),. 37-46.

23. Lyashenko, V., & et al.. (2021). Modern Walking Robots: A Brief Overview. International Journal of Recent Technology and Applied Science, 3(2), 32-39.

24. Sotnik, S., & et al.. (2022). Overview of Innovative Walking Robots. International Journal of Academic Engineering Research, 6(4), 3-7.

25. Sotnik, S., & et al.. (2022). Agricultural Robotic Platforms. International Journal of Academic Engineering Research, 6(4), 14-21.

26. Maksymova, S., Matarneh, R., & Lyashenko, V. V. (2017). Software for Voice Control Robot: Example of Implementation. Open Access Library Journal, 4, e3848.

27. Attar, H., Abu-Jassar, A. T., Lyashenko, V., Al-qerem, A., Sotnik, S., Alharbi, N., & Solyman, A. A. (2023). Proposed synchronous electric motor simulation with built-in permanent magnets for robotic systems. SN Applied Sciences, 5(6), 160.

28. Kuzemin, A., Lуashenko, V., Bulavina, E., & Torojev, A. (2005). Analysis of movement of financial flows of economical agents as the basis for designing the system of economical security (general conception). In Third international conference «Information research, applications, and education (pp. 27-30).

29. Lyashenko, V., Ahmad, M. A., Sotnik, S., Deineko, Z., & Khan, A. (2018). Defects of communication pipes from plastic in modern civil engineering. International Journal of Mechanical and Production Engineering Research and Development, 8(1), 253-262.

30. Al-Sherrawi, M. H., Lyashenko, V., Edaan, E. M., & Sotnik, S. (2018). Corrosion as a source of destruction in construction. International Journal of Civil Engineering and Technology, 9(5), 306-314.

31. Ahmad, M. A., Baker, J. H., Tvoroshenko, I., Kochura, L., & Lyashenko, V. (2020). Interactive Geoinformation Three-Dimensional Model of a Landscape Park Using Geoinformatics Tools. International Journal on Advanced Science, Engineering and Information Technology, 10(5), 2005-2013.

32. Khan, A., Joshi, S., Ahmad, M. A., & Lyashenko, V. (2015). Some effect of Chemical treatment by Ferric Nitrate salts on the structure and morphology of Coir Fibre Composites. Advances in Materials Physics and Chemistry, 5(1), 39-45.

33. Lyashenko, V. V., Lyubchenko, V. A., Ahmad, M. A., Khan, A., & Kobylin, O. A. (2016). The Methodology of Image Processing in the Study of the Properties of Fiber as a Reinforcing Agent in Polymer Compositions. International Journal of Advanced Research in Computer Science, 7(1).

34. Tahseen A. J. A., & et al.. (2023). Binarization Methods in Multimedia Systems when Recognizing License Plates of Cars. International Journal of Academic Engineering Research (IJAER), 7(2), 1-9.

35. Abu-Jassar, A. T., Attar, H., Amer, A., Lyashenko, V., Yevsieiev, V., & Solyman, A. (2024). Remote Monitoring System of Patient Status in Social IoT Environments Using Amazon Web Services (AWS) Technologies and Smart Health Care. International Journal of Crowd Science.

36. Abu-Jassar, A. T., Attar, H., Amer, A., Lyashenko, V., Yevsieiev, V., & Solyman, A. (2024). Development and Investigation of Vision System for a Small-Sized Mobile Humanoid Robot in a Smart Environment. International Journal of Crowd Science.

37. Color correction of the input image as an element of improving the quality of its visualization / M. Yevstratov, V. Lyubchenko, Abu-Jassar Amer, V. Lyashenko // Technical science research in Uzbekistan. – 2024. – № 2(4). – P. 79-88.

38. Drugarin, C. V. A., Lyashenko, V. V., Mbunwe, M. J., & Ahmad, M. A. (2018). Pre-processing of Images as a Source of Additional Information for Image of the Natural Polymer Composites. Analele Universitatii'Eftimie Murgu', 25(2).

39. Lyubchenko, V., Veretelnyk, K., Kots, P., & Lyashenko, V. (2024).Digital image segmentation procedure as an example of an NP-problem. Multidisciplinary Journal of Science and Technology, 4(4), 170-177.

40. Abu-Jassar, A., Al-Sharo, Y., Boboyorov, S., & Lyashenko, V. (2023, December). Contrast as a Method of Image Processing in Increasing Diagnostic Efficiency When Studying Liver Fatty Tissue Levels. In 2023 2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence (EICEEAI) (pp. 1-5). IEEE.

41. Kroemer, O., & et al. (2021). A review of robot learning for manipulation: Challenges, representations, and algorithms. Journal of machine learning research, 22(30), 1-82.

42. Nair, S., & et al. (2022). R3m: A universal visual representation for robot manipulation. arXiv preprint arXiv:2203.12601.

43. Adamkiewicz, M., & et al. (2022). Vision-only robot navigation in a neural radiance world. IEEE Robotics and Automation Letters, 7(2), 4606-4613.

44. Bonci, A., & et al. (2021). Human-robot perception in industrial environments: A survey. Sensors, 21(5), 1571.

45. Aguiar, A. S., & et al. (2020). Localization and mapping for robots in agriculture and forestry: A survey. Robotics, 9(4), 97.

46. Rosen, D. M., & et al. (2021). Advances in inference and representation for simultaneous localization and mapping. Annual Review of Control, Robotics, and Autonomous Systems, 4(1), 215-242.