Development of programmed trajectories based on the mobility degrees of manipulation robot with a spherical coordinate system for removing oxide film in the production of commercial magnesium

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.298912

Keywords:

foundry conveyor, oxide film, manipulation robot, trajectory planning, quadratic interpolation

Abstract

The object of this study is to robotize the technological operation of removing the oxide film from the surface of a magnesium melt poured into continuously moving molds of a casting conveyor for the production of commercial magnesium. To robotize this technological operation, it is proposed to use a two-armed manipulation robot with a spherical coordinate system, which has six degrees of mobility. Software trajectories have been developed according to the degrees of mobility of the manipulation robot in terms of position, speed, and acceleration to perform the technological operation of removing the oxide film from the surface of the magnesium melt poured into the moving molds of the foundry conveyor. Programmed trajectories are described by quadratic polynomials that satisfy restrictions on the values of the generalized coordinate, velocity, and acceleration. These limitations are determined by the design features and energy capabilities of the degrees of mobility drives of the manipulation robot. Programmed trajectories along the first and second degrees of freedom compensate for the continuous movement of the molds of the foundry conveyor. Programmed trajectories along the third and fourth degrees of mobility enable the collection of the oxide film from the surface of the magnesium melt. Programmed trajectories along the fifth and sixth degrees of freedom enable the discharge of the collected oxide film into a special container. The reliability of the developed programmed trajectories is confirmed by the simulation results using MATLAB version R2015b. Based on the results, a cyclogram for controlling a manipulation robot has been constructed to perform the technological operation of removing the oxide film in the production of commercial magnesium. The results could be used in the robotization of technological processes for removing the oxide film in the production of commercial magnesium or similar foundries

Author Biographies

Akambay Beisembayev, Satbayev University

PhD, Associate Professor

Department of Automation and Control

Anargul Yerbossynova, Satbayev University

Doctoral Student

Department of Automation and Control

Petro Pavlenko, National Aviation University

Doctor of Technical Sciences, Professor

Department of Applied Mechanics and Materials Engineering

Mukhit Baibatshayev, Satbayev University

Doctor of Technical Sciences, Associate Professor

Department of Automation and Control

References

  1. Lebedev, V. A., Sedyh, V. I. (2010). Metallurgiya magniya. Ekaterinburg: UGTU-UPI, 174.
  2. Yanushevskiy, A. S., Korshunov, V. V. (2017). Proizvodstvo magnievyh otlivok v metallicheskie formy. Omskiy nauchnyy vestnik. Mashinostroenie, mashinovedenie, 1 (151), 45–48.
  3. Beisembayev, A., Yerbossynova, A., Pavlenko, P., Baybatshaev, M. (2023). Development of a software trajectory of a manipulation robot for removing oxide film in the production of commercial magnesium. KazATC Bulletin, 127 (4), 160–169. https://doi.org/10.52167/1609-1817-2023-127-4-160-169
  4. Beisembayev, A., Yerbossynova, A., Pavlenko, P., Baibatshayev, M. (2023). Planning trajectories of a manipulation robot with a spherical coordinate system for removing oxide film in the production of commercial lead, zinc. Eastern-European Journal of Enterprise Technologies, 4 (2 (124)), 80–89. https://doi.org/10.15587/1729-4061.2023.286463
  5. Ross, L. T., Fardo, S. W., Walach, M. F. (2018). Industrial robotics fundamentals: theory and applications. The Goodheart-Willcox Company, Inc., 463 p.
  6. Ruiz-Celada, O., Verma, P., Diab, M., Rosell, J. (2022). Automating Adaptive Execution Behaviors for Robot Manipulation. IEEE Access, 10, 123489–123497. https://doi.org/10.1109/access.2022.3223995
  7. Akbari, A., Lagriffoul, F., Rosell, J. (2018). Combined heuristic task and motion planning for bi-manual robots. Autonomous Robots, 43 (6), 1575–1590. https://doi.org/10.1007/s10514-018-9817-3
  8. Xu, S., Ou, Y., Duan, J., Wu, X., Feng, W., Liu, M. (2019). Robot trajectory tracking control using learning from demonstration method. Neurocomputing, 338, 249–261. https://doi.org/10.1016/j.neucom.2019.01.052
  9. Biagiotti, L., Melchiorri, C. (2019). Trajectory generation via FIR filters: A procedure for time-optimization under kinematic and frequency constraints. Control Engineering Practice, 87, 43–58. https://doi.org/10.1016/j.conengprac.2019.03.017
  10. Faroni, M., Beschi, M., Visioli, A., Pedrocchi, N. (2021). A real-time trajectory planning method for enhanced path-tracking performance of serial manipulators. Mechanism and Machine Theory, 156, 104152. https://doi.org/10.1016/j.mechmachtheory.2020.104152
  11. Dai, H., Lu, Z., He, M., Yang, C. (2023). A Gripper-like Exoskeleton Design for Robot Grasping Demonstration. Actuators, 12 (1), 39. https://doi.org/10.3390/act12010039
  12. Kazim, I. J., Tan, Y., Qaseer, L. (2021). Integration of DE Algorithm with PDC-APF for Enhancement of Contour Path Planning of a Universal Robot. Applied Sciences, 11 (14), 6532. https://doi.org/10.3390/app11146532
  13. Wu, G., Zhao, W., Zhang, X. (2020). Optimum time-energy-jerk trajectory planning for serial robotic manipulators by reparameterized quintic NURBS curves. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 235 (19), 4382–4393. https://doi.org/10.1177/0954406220969734
  14. Wang, L., Xiang, Y., Fox, D. (2020). Manipulation Trajectory Optimization with Online Grasp Synthesis and Selection. Robotics: Science and Systems XVI. https://doi.org/10.15607/rss.2020.xvi.033
  15. Su, C., Zhang, S., Lou, S., Wang, R., Cao, G., Yang, L., Wang, Q. (2020). Trajectory coordination for a cooperative multi-manipulator system and dynamic simulation error analysis. Robotics and Autonomous Systems, 131, 103588. https://doi.org/10.1016/j.robot.2020.103588
  16. Goritov, A. N., Goncharov, K. V. (2020). Motion trajectory planning for a multi-link manipulator in an unknown environment based on ant colony optimization. Proceedings of Tomsk State University of Control Systems and Radioelectronics, 23 (2), 55–64. https://doi.org/10.21293/1818-0442-2020-23-2-55-64
  17. Merlo, F., Vazzoler, G., Berselli, G. (2023). Eco-programming of industrial robots for sustainable manufacturing via dynamic time scaling of trajectories. Robotics and Computer-Integrated Manufacturing, 79, 102420. https://doi.org/10.1016/j.rcim.2022.102420
  18. Benotsmane, R., Dudás, L., Kovács, G. (2020). Trajectory Optimization of Industrial Robot Arms Using a Newly Elaborated “Whip-Lashing” Method. Applied Sciences, 10 (23), 8666. https://doi.org/10.3390/app10238666
  19. Ostanin, M., Popov, D., Klimchik, A. (2018). Programming by Demonstration Using Two-Step Optimization for Industrial Robot. IFAC-PapersOnLine, 51 (11), 72–77. https://doi.org/10.1016/j.ifacol.2018.08.237
  20. French, K. D., Kim, J. H., Du, Y., Goeddel, E. M., Zeng, Z., Jenkins, O. C. (2023). Super Intendo: Semantic Robot Programming from Multiple Demonstrations for taskable robots. Robotics and Autonomous Systems, 166, 104397. https://doi.org/10.1016/j.robot.2023.104397
Development of programmed trajectories based on the mobility degrees of manipulation robot with a spherical coordinate system for removing oxide film in the production of commercial magnesium

Downloads

Published

2024-02-28

How to Cite

Beisembayev, A., Yerbossynova, A., Pavlenko, P., & Baibatshayev, M. (2024). Development of programmed trajectories based on the mobility degrees of manipulation robot with a spherical coordinate system for removing oxide film in the production of commercial magnesium. Eastern-European Journal of Enterprise Technologies, 1(1 (127), 67–88. https://doi.org/10.15587/1729-4061.2024.298912

Issue

Section

Engineering technological systems