Five-axis parallel mechanism system (PMS) CNC partial link control system based on modified inverse kinematic of 6-DOF UPS parallel manipulator

Nur Jamiludin Ramadhan; Indrawanto Indrawanto; Hoe Dinh Nguyen; Nur Jamiludin Ramadhan; Indrawanto Indrawanto; Hoe Dinh Nguyen

doi:10.14203/j.mev.2023.v14.1-10

Five-axis parallel mechanism system (PMS) CNC partial link control system based on modified inverse kinematic of 6-DOF UPS parallel manipulator

Nur Jamiludin Ramadhan, Indrawanto Indrawanto, Hoe Dinh Nguyen

Abstract

This paper presents a control system algorithm for a five-axis parallel mechanism system (PMS) CNC milling machine based on a 6-DOF Stewart platform parallel manipulator with a universal-prismatic-spherical (UPS) configuration. The control system reads the G-Code commands as standard CNC machine language, then extract data points and interpolates them to generate the robot trajectory patterns as motion references. Then, the control system uses the modified inverse kinematic equation to determine the length of each link to move the end effector to track the trajectory patterns from the previous G-code extraction process. The inverse kinematic equation is modified especially for the five-axis PMS CNC milling machine by including machine-offset and tools-offset parameters so it will be easier for the control system to implement the kinematic equation. As expected, the system simulation results successfully followed the G-Code program moving commands. The average error of the length control system is 0,1 mm, while the average error of the length change rate control system is 1,8 mm/s. The maximum error is 26.9 mm was caused by the system's inability to follow the motion profile in transient. It can be concluded that 6-DOF Stewart platform parallel structures,which provide better performance than serial structures, can be implemented as a new concept for the motion mechanism of five-axis CNC milling machines. The five-axis PMS CNC milling machine also promises better performance than conventional five-axis gantry structures CNC.

10.14203/j.mev.2023.v14.1-10

Keywords

Stewart platform; parallel manipulator; parallel mechanism structure; machine tools; CNC control system

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References

Ratiu, M. & Anton, D. M., “A brief overview of parallel robots and parallel kinematic machines,” Materials Science and Engineering. 898. 012007, 2020.

Yi, J., Qingqing, H., Zhaoen, D. et al., “Structural design and kinematic analysis of a welding robot for liquefied natural gas membrane tank automatic welding,” Int J Adv Manuf Technol, 122, 461–474, 2022.

Nzue, R., Brethé, J., et al. Comparison of serial and parallel robot repeatability based on different performance criteria,” Mechanism and Machine Theory, 61, 136-155, 2013.

Nguyen Vu, L., & Kuo, C., “An analytical stiffness method for spring-articulated planar serial or quasi-serial manipulators under gravity and an arbitrary load,” Mechanism and Machine Theory, 137, 108-126, 2019.

Ramadhan, N. J., Lilansa, N., Rifa'i, A., & Nguyen Dinh, H., “Pattern recognition based movement control and gripping forces control system on arm robot model using LabVIEW,”

Journal of Mechatronics, Electrical Power, and Vehicular Technology, 13(1), 1-14, 2022.

Darvekar, S., Koteswara Rao, A., & Shankar Ganesh, S., “Machining capability of a 2-D of parallel kinematic machine tool and conventional CNC milling machine,” Materials Today:

Proceedings, 45, 3213-3218, 2021.

Stepanenko, O., Bonev Ilian, A., & Zlatanov, D., “A new 4-DOF fully parallel robot with decoupled rotation for five-axis micromachining applications,” ASME. J. Mechanisms Robotics,

June 2019; 11(3): 031010, 2019.

Fu, R., Jin, Y., et al., “Review on structure-based errors of parallel kinematic machines in comparison with traditional nc machines,” Springer Comm Comp Inf Sci, 923, 2018.

Verl, A., Valente, A., Melkote, S., Brecher, C., Ozturk, E., & Tunc, L. T.,” Robots in machining. CIRP Annals, 68(2), 799-822, 2019.

Wang, W., Wang, N., & Wu, X., “Kinematics and dynamics analysis of a six-degree of freedom parallel manipulator,” International Journal of Advanced Robotic Systems, 2022.

Zhao, Y., & Gao, F., “ Inverse dynamics of the 6-dof out-parallel manipulator by means of the principle of virtual work”, Robotica, 27(2), 259-268, 2009.

Cao, W., Ding, H., & Zhu, W., “Stiffness modeling of overconstrained parallel mechanisms under considering gravity and external payloads,” Mechanism and Machine Theory, 135, 1-16, 2019.

Yang, D., Xie, F. & Liu, X., “Velocity constraints based approach for online trajectory planning of high-speed parallel robots,” Chin. J. Mech. Eng., 35, 127, 2022.

Lin, J., Qi, C., Gao, F., Yue, Y., Hu, Y., & Wei, B., “Modeling and verification for a 3-DOF flexure-based planar parallel micromanipulator,” ASME. J. Mechanisms Robotics, 2022.

Chen, G., Rui, X., Abbas, L. K., Wang, G., Yang, F., & Zhu, W., “A novel method for the dynamic modeling of Stewart parallel mechanism,” Mechanism and Machine Theory, 126, 397-412,

Brinker, J., Corves, B., & Takeda, Y., “Kinematic performance evaluation of high-speed Delta parallel robots based on motion/force transmission indices,” Mechanism and Machine

Theory, 125, 111-125, 2018.

Velasco, J., Barambones, Ó., Calvo, I., Venegas, P., & Napole, C. M., “Validation of a Stewart platform inspection system with an artificial neural network controller,” Precision Engineering, 74, 369-381, 2022.

Xi, F., Moosavian, A., et al., “Analysis and control of an actuation-redundant parallel mechanism requiring synchronization,” ASME. J. Mech. Rob., 12(4), 044501, 2020.

Xu, L., Chai, X., et al., “Design and experimental investigation of a new 2R1T Overconstrained Parallel Kinematic Machine with Actuation Redundancy,” ASME J. Mech. Rob., 11(3), 031016, 2019.

Silva, D., Garrido, J., & Riveiro, E., “Stewart platform motion control automation with industrial resources to perform cycloidal and oceanic wave trajectories. machines,” 10(8), 711, 2022.

Jin, X., Jung, J., Ko, S., Choi, E., Park, J.-O., & Kim, C.-S., “Geometric parameter calibration for a cable-driven parallel robot based on a single one-dimensional laser distance sensor measurement and experimental modeling, Sensors, 18(7), 2392, 2018.

Bilal, D. K., Unel, M., Tunc, L. T., & Gonul, B., “Development of a vision based pose estimation system for robotic machining and improving its accuracy using LSTM neural networks and sparse regression,” Robotics and Computer-Integrated Manufacturing, 74, 102262, 2022.

Danaei, B., Arian, A., Masouleh, M.T., Kalhor, A., “Kinematic and dynamic modeling and base inertial parameters determination of the quadrupteron parallel manipulator,” Computational Kinematics, Mechanisms and Machine Science, vol 50. Springer, Cham, 2018.

Pham, M., Champliaud, H., Liu, Z., & Bonev, I. A., “Parameterized finite element modeling and experimental modal testing for vibration analysis of an industrial hexapod

for machining,” Mechanism and Machine Theory, 167, 104502, 2022.

Stabile, A., Yotov, V. V., Aglietti, G. S., De Francesco, P., & Richardson, G., “Effect of boundary conditions on a highperformance isolation hexapod platform,” Mechanism and

Machine Theory, 177, 105020, 2022.

Barnfather, J.D., Goodfellow, M.J. & Abram, T., “Achievable tolerances in robotic feature machining operations using a low-cost hexapod,” Int J Adv Manuf Technol, 95, 1421–1436, 2018.

Indrawanto & Anindito, S., “Design and control of the Stewart platform robot,” Third Asia International Conference on Modelling & Simulation, 475-480, 2009.