DOI : https://doi.org/10.18517/ijaseit.12.6.16591

Performance Analysis of 4-DOF RPRR Robot Manipulator Actuation Strategy for Pick and Place Application in Healthcare Environment

Hadha Afrisal (1), Ahmad Didik Setiyadi (2), Munawar Agus Riyadi (3), Rifky Ismail (4), Olimjon Toirov (5), Iwan Setiawan (6)
(1) Department of Electrical Engineering, Faculty of Engineering, Universitas Diponegoro, Tembalang, Semarang, 50275, Indonesia
(2) Department of Electrical Engineering, Faculty of Engineering, Universitas Diponegoro, Tembalang, Semarang, 50275, Indonesia
(3) Department of Electrical Engineering, Faculty of Engineering, Universitas Diponegoro, Tembalang, Semarang, 50275, Indonesia
(4) Department of Mechanical Engineering, Faculty of Engineering, Universitas Diponegoro, Tembalang, Semarang, 50275, Indonesia
(5) Department of Electrical Machine, Tashkent State Technical University, Tashkent, 100095, Uzbekistan
(6) Department of Electrical Engineering, Faculty of Engineering, Universitas Diponegoro, Tembalang, Semarang, 50275, Indonesia
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How to cite (IJASEIT) :
Afrisal, Hadha, et al. “Performance Analysis of 4-DOF RPRR Robot Manipulator Actuation Strategy for Pick and Place Application in Healthcare Environment”. International Journal on Advanced Science, Engineering and Information Technology, vol. 12, no. 6, Nov. 2022, pp. 2258-65, doi:10.18517/ijaseit.12.6.16591.
Citation Format :
Direct and indirect physical contact of humans and objects become the main medium of transmissible diseases such as COVID-19. Some strategies have been proposed to mitigate the risks of infections by minimizing physical contact, such as using robotics technology. Tele-robotics is one of the sub-fields in robotics that aims to implement physical surrogates for monitoring and controlling robots from remote distances, either autonomous, semi-autonomous, or manually guided. This paper discusses experimental research for evaluating the performance of a 4-DOF robot manipulator for pick and place tasks on small medical objects, such as test tubes in table-top scenarios. The robot manipulator is designed as an RPRR manipulator and is equipped with a gripper attached to its end-effector. Inverse kinematics and trajectory planning methods have been successfully implemented in real-time. The inverse kinematic method utilizes a pseudo-inverse Jacobian solver, and the trajectory generation utilizes a sigmoid function. The performance analysis results show that pick and place missions have been demonstrated with minimum tolerable position error, which is not more than 3.5 mm. The robot manipulator can satisfy high precision during repetitive experiments and maintain its accuracy in picking and placing standard test tubes from one rack to another within its working space. The smooth trajectories of the end-effector are achieved by implementing the sigmoid function. Thus, it satisfies the requirement for handling objects with minimum vibrations even during the actuation process with maximum speed.

W. H. Gan, J. W. Lim, and D. Koh, “Preventing Intra-hospital Infection and Transmission of Coronavirus Disease 2019 in Health-care Workers,” Safety and Health at Work, vol. 11, no. 2, 2020, doi: 10.1016/j.shaw.2020.03.001.

M. Bongiovanni and F. Basile, “Re-infection by COVID-19: a real threat for the future management of pandemia?,” Infectious Diseases, vol. 52, no. 8. 2020. doi: 10.1080/23744235.2020.1769177.

T. Haidegger et al., “Industrial and Medical Cyber-Physical Systems: Tackling User Requirements and Challenges in Robotics,” 2020. doi: 10.1007/978-3-030-14350-3_13.

G. Yang et al., “Keep Healthcare Workers Safe: Application of Teleoperated Robot in Isolation Ward for COVID-19 Prevention and Control,” Chinese Journal of Mechanical Engineering (English Edition), vol. 33, no. 1, 2020, doi: 10.1186/s10033-020-00464-0.

S. Mehrdad, F. Liu, M. T. Pham, A. Leleví©, and S. Farokh Atashzar, “Review of advanced medical telerobots,” Applied Sciences (Switzerland), vol. 11, no. 1. 2021. doi: 10.3390/app11010209.

C. Tamantini, F. Scotto Di Luzio, F. Cordella, G. Pascarella, F. E. Agro, and L. Zollo, “A Robotic Health-Care Assistant for COVID-19 Emergency: A Proposed Solution for Logistics and Disinfection in a Hospital Environment,” IEEE Robotics and Automation Magazine, vol. 28, no. 1, 2021, doi: 10.1109/MRA.2020.3044953.

H. Zhang et al., “Research on intelligent robot systems for emergency prevention and control of major pandemics,” Scientia Sinica Informationis, vol. 50, no. 7. 2020. doi: 10.1360/SSI-2020-0107.

M. Tavakoli, J. Carriere, and A. Torabi, “Robotics, Smart Wearable Technologies, and Autonomous Intelligent Systems for Healthcare During the COVID”19 Pandemic: An Analysis of the State of the Art and Future Vision,” Advanced Intelligent Systems, vol. 2, no. 7, 2020, doi: 10.1002/aisy.202000071.

S. D. Sierra Marí­n et al., “Expectations and Perceptions of Healthcare Professionals for Robot Deployment in Hospital Environments During the COVID-19 Pandemic,” Frontiers in Robotics and AI, vol. 8, 2021, doi: 10.3389/frobt.2021.612746.

P. Khalaf and H. Richter, “Trajectory Optimization of Robots with Regenerative Drive Systems: Numerical and Experimental Results,” IEEE Transactions on Robotics, vol. 36, no. 2, 2020, doi: 10.1109/TRO.2019.2923920.

R. Campa and J. Bernal, “Analysis of the different conventions of Denavit-Hartenberg parameters,” International Review on Modelling and Simulations, vol. 12, no. 1, 2019, doi: 10.15866/iremos.v12i1.13623.

A. El-Sherbiny, M. A. Elhosseini, and A. Y. Haikal, “A comparative study of soft computing methods to solve inverse kinematics problem,” Ain Shams Engineering Journal, vol. 9, no. 4, 2018, doi: 10.1016/j.asej.2017.08.001.

M. Husty, I. Birlescu, P. Tucan, C. Vaida, and D. Pisla, “An algebraic parameterization approach for parallel robots analysis,” Mechanism and Machine Theory, vol. 140, 2019, doi: 10.1016/j.mechmachtheory.2019.05.024.

S. C. Zhen, Z. Zhao, X. Liu, F. Chen, H. Zhao, and Y. H. Chen, “A Novel Practical Robust Control Inheriting PID for SCARA Robot,” IEEE Access, 2020, doi: 10.1109/ACCESS.2020.3045789.

M. Crenganis, A. Barsan, M. Tera, and A. Chicea, “Dynamic analysis of a five degree of freedom robotic arm using MATLAB-Simulink Simscape,” MATEC Web of Conferences, vol. 343, 2021, doi: 10.1051/matecconf/202134308004.

Z. Liao, G. Jiang, F. Zhao, X. Mei, and Y. Yue, “A novel solution of inverse kinematic for 6R robot manipulator with offset joint based on screw theory,” International Journal of Advanced Robotic Systems, vol. 17, no. 3, 2020, doi: 10.1177/1729881420925645.

T. Liu et al., “Iterative Jacobian-Based Inverse Kinematics and Open-Loop Control of an MRI-Guided Magnetically Actuated Steerable Catheter System,” IEEE/ASME Transactions on Mechatronics, vol. 22, no. 4, 2017, doi: 10.1109/TMECH.2017.2704526.

J. Demby’S, Y. Gao, and G. N. Desouza, “A Study on Solving the Inverse Kinematics of Serial Robots using Artificial Neural Network and Fuzzy Neural Network,” in IEEE International Conference on Fuzzy Systems, 2019, vol. 2019-June. doi: 10.1109/FUZZ-IEEE.2019.8858872.

E. Shahabi and C. H. Kuo, “Solving inverse kinematics of a planar dual-backbone continuum robot using neural network,” in Mechanisms and Machine Science, 2019, vol. 59. doi: 10.1007/978-3-319-98020-1_42.

D. Deshmukh, D. K. Pratihar, A. K. Deb, H. Ray, and A. Ghosh, “ANFIS-Based Inverse Kinematics and Forward Dynamics of 3 DOF Serial Manipulator,” in Advances in Intelligent Systems and Computing, 2021, vol. 1375 AIST. doi: 10.1007/978-3-030-73050-5_15.

Y. Chen, X. Luo, B. Han, Y. Jia, G. Liang, and X. Wang, “A general approach based on Newton’s method and cyclic coordinate descent method for solving the inverse kinematics,” Applied Sciences (Switzerland), vol. 9, no. 24, 2019, doi: 10.3390/app9245461.

M. K. Mishra, S. Ghosal, A. K. Samantaray, and G. Chakraborty, “Jacobian-Based Inverse Kinematics Analysis of a Pneumatic Actuated Continuum Manipulator,” 2021. doi: 10.1007/978-981-16-1769-0_1.

M. Dalvi, S. S. Chiddarwar, S. R. Sahoo, and M. R. Rahul, “Dual Quaternion-Based Kinematic Modelling of Serial Manipulators,” 2021. doi: 10.1007/978-981-15-3639-7_1.

Y. Fang, J. Hu, W. Liu, Q. Shao, J. Qi, and Y. Peng, “Smooth and time-optimal S-curve trajectory planning for automated robots and machines,” Mechanism and Machine Theory, vol. 137, 2019, doi: 10.1016/j.mechmachtheory.2019.03.019.

J. Kim, M. Jin, S. H. Park, S. Y. Chung, and M. J. Hwang, “Task space trajectory planning for robot manipulators to follow 3-d curved contours,” Electronics (Switzerland), vol. 9, no. 9, 2020, doi: 10.3390/electronics9091424.

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