DEVELOPMENT OF A PROGRAM FOR PROCESSING 3D MODELS OF  OBJECTS IN A COLLABORATIVE ROBOT WORKSPACE USING AN HD  CAMERA

Vladyslav Yevsieiev; Svitlana Maksymova; Ahmad Alkhalaileh; Ahmad Alkhalaileh; Dmytro  Gurin1

Authors

Vladyslav Yevsieiev 1Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine
Svitlana Maksymova 1Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine
Ahmad Alkhalaileh Senior Developer Electronic Health Solution, Amman, Jordan
Ahmad Alkhalaileh Senior Developer Electronic Health Solution, Amman, Jordan
Dmytro Gurin1 Department of Computer-Integrated Technologies, Automation and Robotics, Kharkiv National University of Radio Electronics, Ukraine

Keywords:

Industry 5.0, 3D Model Processing, Collaborative Robot, Manipulator, Hd Camera, Point Cloud, Object Recognition.

Abstract

This article presents the research of methods for program development for
processing 3D models of objects in a collaborative robot workspace using an HD
camera. The features of creating and processing a point cloud in real time under
different lighting conditions and image refresh rates are considered, and the influence
of these factors on the accuracy of object recognition is also assessed. The presented
experimental results show the optimal settings to ensure stable operation of the system
in various production conditions. The proposed methodology allows to increase the
accuracy and speed of the manipulator operation due to improved visual processing of
images and 3D models.

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. Yevsieiev, V., & et al. (2024). Research of Existing Methods of Representing a Collaborative Robot-Manipulator Environment within the Framework of Cyber-Physical Production Systems. Multidisciplinary Journal of Science and Technology, 4(9), 112-120.

3. Maksymova, S., & et al. (2024). Comparative Analysis of methods for Predicting the Trajectory of Object Movement in a Collaborative Robot-Manipulator Working Area. Multidisciplinary Journal of Science and Technology, 4(10), 38-48.

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

5. Yevsieiev, V., & et al. (2024). Human Operator Identification in a Collaborative Robot Workspace within the Industry 5.0 Concept. Multidisciplinary Journal of Science and Technology, 4(9), 95-105.

6. Nevliudov, I., & et al. (2023). A Small-Sized Robot Prototype Development Using 3D Printing. CAD In Machinery Design Implementation and Educational Issues (CADMD'2023) : proceedings of the XXXI International Conference, Suprasl, 12.

7. 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.

8. 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.

9. Matarneh, R., Maksymova, S., Deineko, Z., & Lyashenko, V. (2017). Building robot voice control training methodology using artificial neural net. International Journal of Civil Engineering and Technology, 8(10), 523-532.

10. Lyashenko, V., Kobylin, O., & Ahmad, M. A. (2014). General methodology for implementation of image normalization procedure using its wavelet transform. International Journal of Science and Research (IJSR), 3(11), 2870-2877.

11. Sotnik, S., Matarneh, R., & Lyashenko, V. (2017). System model tooling for injection molding. International Journal of Mechanical Engineering and Technology, 8(9), 378-390.

12. Maksymova, S., Matarneh, R., Lyashenko, V. V., & Belova, N. V. (2017). Voice Control for an Industrial Robot as a Combination of Various Robotic Assembly Process Models. Journal of Computer and Communications, 5, 1-15.

13. Гиренко, А. В., Ляшенко, В. В., Машталир, В. П., & Путятин, Е. П. (1996). Методы корреляционного обнаружения объектов. Харьков: АО “БизнесИнформ, 112.

14. Lyashenko, V. V., Babker, A. M. A. A., & Kobylin, O. A. (2016). The methodology of wavelet analysis as a tool for cytology preparations image processing. Cukurova Medical Journal, 41(3), 453-463.

15. Lyashenko, V. V., Matarneh, R., & Deineko, Z. V. (2016). Using the Properties of Wavelet Coefficients of Time Series for Image Analysis and Processing. Journal of Computer Sciences and Applications, 4(2), 27-34.

16. Lyashenko, V., Matarneh, R., & Kobylin, O. (2016). Contrast modification as a tool to study the structure of blood components. Journal of Environmental Science, Computer Science and Engineering & Technology, 5(3), 150-160.

17. Lyubchenko, V., & et al.. (2016). Digital image processing techniques for detection and diagnosis of fish diseases. International Journal of Advanced Research in Computer Science and Software Engineering, 6(7), 79-83.

18. Lyashenko, V. V., Matarneh, R., Kobylin, O., & Putyatin, Y. P. (2016). Contour Detection and Allocation for Cytological Images Using Wavelet Analysis Methodology. International Journal, 4(1), 85-94.

19. Ahmad, M. A., Baker, J. H., Tvoroshenko, I., & Lyashenko, V. (2019). Modeling the structure of intellectual means of decision-making using a system-oriented NFO approach. International Journal of Emerging Trends in Engineering Research, 7(11), 460-465.

20. Lyashenko, V., Kobylin, O., & Selevko, O. (2020). Wavelet analysis and contrast modification in the study of cell structures images. International Journal of Advanced Trends in Computer Science and Engineering, 9(4), 4701-4706.

21. Lyashenko, V., & et al.. (2021). Wavelet ideology as a universal tool for data processing and analysis: some application examples. International Journal of Academic Information Systems Research (IJAISR), 5(9), 25-30.

22. 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.

23. Lyashenko, V. V., Matarneh, R., & Deineko, Z. V. (2016). Using the Properties of Wavelet Coefficients of Time Series for Image Analysis and Processing. Journal of Computer Sciences and Applications, 4(2), 27-34.

24. Babker, A. M., Abd Elgadir, A. A., Tvoroshenko, I., & Lyashenko, V. (2019). Information technologies of the processing of the spaces of the states of a complex biophysical object in the intellectual medical system health. International Journal of Advanced Trends in Computer Science and Engineering, 8(6), 3221-3227.

25. 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.

26. Gurin, D., & et al. (2024). Using Convolutional Neural Networks to Analyze and Detect Key Points of Objects in Image. Multidisciplinary Journal of Science and Technology, 4(9), 5-15.

27. Abu-Jassar, A., & et al. (2024). The Optical Flow Method and Graham’s Algorithm Implementation Features for Searching for the Object Contour in the Mobile Robot’s Workspace. Journal of Universal Science Research, 2(3), 64-75.

28. Gurin, D., & et al. (2024). Effect of Frame Processing Frequency on Object Identification Using MobileNetV2 Neural Network for a Mobile Robot. Multidisciplinary Journal of Science and Technology, 4(8), 36-44.

29. Chala, O., & et al. (2024). Switching Module Basic Concept. Multidisciplinary Journal of Science and Technology, 4(7), 87-94.

30. Gurin, D., & et al. (2024). MobileNetv2 Neural Network Model for Human Recognition and Identification in the Working Area of a Collaborative Robot. Multidisciplinary Journal of Science and Technology, 4(8), 5-12.

31. 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.

32. 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.

33. 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.

34. 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.

35. 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.

36. Orobinskyi, P., Petrenko, D., & Lyashenko, V. (2019, February). Novel approach to computer-aided detection of lung nodules of difficult location with use of multifactorial models and deep neural networks. In 2019 IEEE 15th International Conference on the Experience of Designing and Application of CAD Systems (CADSM) (pp. 1-5). IEEE.

37. Matarneh, R., Sotnik, S., Belova, N., & Lyashenko, V. (2018). Automated modeling of shaft leading elements in the rear axle gear. International Journal of Engineering and Technology (UAE), 7(3), 1468-1473.

38. 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, 8.

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. Babker, A. M., Suliman, R. S., Elshaikh, R. H., Boboyorov, S., & Lyashenko, V. (2024). Sequence of Simple Digital Technologies for Detection of Platelets in Medical Images. Biomedical and Pharmacology Journal, 17(1), 141-152.

41. Yevstratov, M., Lyubchenko, V., Amer, A. J., & Lyashenko, V. (2024). Color correction of the input image as an element of improving the quality of its visualization. Technical science research in Uzbekistan, 2(4), 79-88.

42. 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.

43. Tzampazaki, M., & et al. (2024). Machine Vision—Moving from Industry 4.0 to Industry 5.0. Applied Sciences, 14(4), 1471.

44. Rane, N. (2023). YOLO and Faster R-CNN object detection for smart Industry 4.0 and Industry 5.0: applications, challenges, and opportunities. Available at SSRN 4624206.

45. Wang, H., & et al. (2023). A safety management approach for Industry 5.0′ s human-centered manufacturing based on digital twin. Journal of Manufacturing Systems, 66, 1-12.

46. Rahate, A., & et al. (2023). Employing multimodal co-learning to evaluate the robustness of sensor fusion for industry 5.0 tasks. Soft Computing, 27(7), 4139-4155.

47. Fraga-Lamas, P., & et al. (2022). Mist and edge computing cyber-physical human-centered systems for industry 5.0: A cost-effective IoT thermal imaging safety system. Sensors, 22(21), 8500.

48. Wagner, R., & et al. (2023). IndustrialEdgeML-End-to-end edge-based computer vision systemfor Industry 5.0. Procedia Computer Science, 217, 594-603.