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Modeling and analysis of an RUU Delta Robot using SolidWorks and SimMechanics

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Abstract

This paper illustrates the methodology for modeling, implementing, and controlling an RUU Delta Robot using computer-aided design and simulation software. Specifically, SolidWorks is employed to construct a CAD model with suitable properties, which is then exported to the MATLAB/SimMechanics environment for generating a multibody system block diagram. A PID controller is implemented to control the robot's position and trajectory movement. The study analyzes moment signal graphs at active joints, comparing them with existing research to validate the accuracy of the results. The investigation reveals that the influence of damping coefficients on the robotic dynamics is negligible, with simulation errors less than 0.02% for different end effect masses. Additionally, the study explores the impact of end effect mass on robotic dynamics and trajectory. Simulation results recommend an optimal operating range with an end effect mass of less than 3 kg, ensuring trajectory errors remain below 2%. As the end effect mass increases, a corresponding fluctuation in the robot's trajectory is observed, leading to longer times to reach the designed trajectory. This study provides valuable insights for practical applications, indicating that the proposed simulation approach is instrumental in assessing the performance of the robot controller before its deployment in an actual prototype.

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Availability of data and materials

The data and source code used to support the findings of this study are available from the corresponding author upon request.

References

  1. Clavel R (1988) DELTA, a fast robot with parallel geometry. In: 18th international symposium on industrial robot, Lausane, pp 91–100

  2. Le HN, Le XH (2018) Geometrical design of a RUU type delta robot based on the prescribed workspace. In: 4th international conference on green technology and sustainable development (GTSD), Ho Chi Minh City, Vietnam, pp 359–364. https://doi.org/10.1109/GTSD.2018.8595674

  3. Qing Z, Panfeng W, Jiangping M (2015) Controller parameter tuning of delta robot based on servo identification. Chin J Mech Eng 28:267–275. https://doi.org/10.3901/CJME.2014.1117.169

    Article  Google Scholar 

  4. Linda O, Manic M (2011) Uncertainty-robust design of interval Type-2 fuzzy logic controller for delta parallel robot. IEEE Trans Industr Inf 7(4):661–670. https://doi.org/10.1109/TII.2011.2166786

    Article  Google Scholar 

  5. Sen MA, Bakircloglu V, Kalyoncu M (2017) Modelling and PID control of Scara Robot. In: International conference on engineering technologies (ICENTE), Turkey, pp 1–4

  6. Ibrahim BSKK, Zargoun AMA (2014) Modelling and control of SCARA manipulator. Proc Comput Sci 42:106–113

    Article  Google Scholar 

  7. Olaya J et al (2017) Analysis of 3 RPS robotic platform motion in SimScape and Matlab GUI environment. Int J Appl Eng ISSNN, Res India Public 12(8):1460–1468

    Google Scholar 

  8. Dastjerdi AH, Sheikhi MM, Masouleh MT (2020) A complete analytical solution for the dimensional synthesis of 3-DOF delta parallel robot for a prescribed workspace. Mech Mach Theory 153:103991

    Article  Google Scholar 

  9. Asadi F, Heydai A (2020) Analytical dynamic modeling of Delta robot with experimental verification. Proc Inst Mech Eng Part K J Multi-Body Dyn 234:623–663

    Google Scholar 

  10. Robert L (2016) The Delta parallel robot: kinematics solutions. Mechanical engineering. Ph.D. thesis, Ohio University, Athens, Ohio

  11. Collins J, Chand S, Vanderkop A, Howard D (2021) A review of physics simulators for robotic applications. IEEE Access 9:51416–51431

    Article  Google Scholar 

  12. Tran THT, Nguyen DS, Vo NT, Le HN (2020) Design of delta robot arm based on topology optimization and generative design method. In: 5th international conference on green technology and sustainable development (GTSD), Ho Chi Minh City, Vietnam, pp 157–161. https://doi.org/10.1109/GTSD50082.2020.9303083

  13. Nguyen HQ et al (2015) Influence of models on computed torque of delta spatial parallel robot. In: Proceeding of the 16th Asian Pacific vibration conference (APVC. 2015), pp 791–798

  14. Quang NH, Quyen NV, Hai DT, Hien NN (2020) Dynamic modelling of 3-RUS spatial parallel robot manipulator. Rev Comput Eng Res 7(1):20–26. https://doi.org/10.18488/journal.76.2020.71.20.26

    Article  Google Scholar 

  15. Subson S, Maneetham D, Aung MM (2022) Kinematics simulation and experiment for optimum design of a new prototype parallel robot. Int J Eng Trends Technol 70(10):350–362. https://doi.org/10.14445/22315381/IJETT-V70I10P234

    Article  Google Scholar 

  16. Hussain S, Jamwal PK, Munir MT (2022) Computer-aided teaching using simmechanics and matlab for project-based learning in a robotics course. Int J Soc Robot 14:85–94. https://doi.org/10.1007/s12369-021-00769-7

    Article  Google Scholar 

  17. Damic V, Cohodar M, Kobilica N (2019) Development of dynamic model of robot with parallel structure based on 3D CAD model. Ann DAAAM Proc 30:155–160

    Article  Google Scholar 

  18. Carpin S, Lewis M, Wang J, Balakirsky S (2007) USARSim: a robot simulator for research and education. In: Proceedings IEEE international conference on robotics and automation, pp 1400–1405

  19. Hugo H, Joan L (2020) The forward and inverse kinematics of a Delta robot, Chapter. In: Proceedings of the advances in computer graphics: 37th computer graphics international conference, CGI 2020, Geneva

  20. Chebotar Y et al (2019) Closing the sim-to-real loop: Adapting simulation randomization with real-world experience. Int Conf Robot Autom (ICRA) 2019:8973–8979

    Google Scholar 

  21. Aguero C et al (2015) Inside the virtual robotics challenge: simulating real-time robotic disaster response. IEEE Trans Autom Sci Eng 12:494–506

    Article  Google Scholar 

  22. Goury O, Duriez C (2018) Fast, generic, and reliable control and simulation of soft robots using model order reduction. IEEE Trans Robot 34:1565–1576

    Article  Google Scholar 

  23. Faure F et al (2012) Sofa: a multi-model framework for interactive physical simulation. In: Payan Y (ed) Soft tissue biomechanical modeling for computer-assisted surgery. Springer, Berlin, pp 283–321

    Chapter  Google Scholar 

  24. Le HN, Dang PV, Pham A-D, Vo NT (2020) System identifications of a 2DOF pendulum controlled by QUBE-servo and its unwanted oscillation factors. Arch Mech Eng 67(4):435–450

    Article  Google Scholar 

  25. Cretescu N, Neagoe M, Saulescu R (2023) Dynamic analysis of a delta parallel robot with flexible links and joint clearances. Appl Sci 13(11):6693. https://doi.org/10.3390/app13116693

    Article  Google Scholar 

  26. Falezza F, Vesentini F, Di Flumeri A, Leopardi L, Fiori G, Mistrorigo G, Muradore R (2022) A novel inverse dynamic model for 3-DoF delta robots. Mechatronics 83:102752

    Article  Google Scholar 

  27. Puglisi LJ, Saltaren R, Garcia C, Cardenas P, Moreno H (2017) Implementation of a generic constraint function to solve the direct kinematics of parallel manipulators using Newton–Raphson approach. J Control Eng Appl Inf 19:71–79

    Google Scholar 

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Acknowledgements

The authors would like to thank all members of Mechatronics Division, University of Science and Technology-The University of Da Nang, for their support and feedback.

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No funding was received on this project.

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NTV and HNL contributed equally to this research.

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Correspondence to Nhu Thanh Vo.

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The authors declare that they have no competing interests.

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Le, H.N., Vo, N.T. Modeling and analysis of an RUU Delta Robot using SolidWorks and SimMechanics. Int. J. Dynam. Control (2024). https://doi.org/10.1007/s40435-023-01377-1

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  • DOI: https://doi.org/10.1007/s40435-023-01377-1

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