Effectiveness of Digital Twin Framework for Collaborative Robotic Manipulation

VERSION OF RECORD ONLINE: 18/09/2025

Authors

Corressponding author's email:

khanh.nt@vgu.edu.vn

DOI:

https://doi.org/10.54644/jte.2025.1835

Keywords:

Automation and control engineering, Collaborative robots, Digital twin, Simulation and modeling, Industrial case study

Abstract

This work examines the effectiveness of a digital twin (DT) framework using an industrial pick-and-place case study with a collaborative robotics arm. The problem addressed is the need for improved production process planning and visualization in robotics. The employed method involves creating a DT and evaluating its fidelity to a physical robotic system performing a pick-and-place task. Evaluations included comparing the digital and real robot trajectories, utilizing ISO 9283 performance testing, and analyzing metrics like RMSE, MAPE, and R2. The evaluation shows initial positive results indicating that the proposed DT framework fits the real data well, thus, demonstrates feasibility of this approach. The results can be used to improve the planning and visualization of the production process for collaborative robot arm with 3D printers or adapted for more complex industrial machine tools. These improvements can support the enterprises to spot potential problems before they occur, optimize performance and reduce costs.

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Author Biographies

Quang-Huan Dong, Vietnamese-German University, Vietnam

Quang-Huan Dong received a PhD degree from the TUM School of Engineering and Design, Technical University of Munich, Germany in 2023. He is currently a postdoctoral researcher at the Faculty of Engineering, Vietnamese-German University, Vietnam. His research focuses on factory automation and software engineering.

Email: huan.dq@vgu.edu.vn. ORCID:  https://orcid.org/0000-0002-3085-3464

Tuan-Khanh Nguyen, Vietnamese-German University, Vietnam

Tuan-Khanh Nguyen received the B.S. and M.S. degrees in electronic telecommunication from Can Tho University, Can Tho, Vietnam, in 2010 and Ho Chi Minh University of Technology, Ho Chi Minh City, Vietnam, in 2014, respectively. He got the PhD degree in Electronic and Computer Engineering at National Taiwan University of Science and Technology in 2023. He is currently pursuing a postdoctoral degree at the Vietnamese-German University. His research interests include semiconductors, radio-frequency biomedical sensors, noncontact vital-sign radar sensors, and microwave circuits and modules.

Email: khanh.nt@vgu.edu.vn. ORCID:  https://orcid.org/0000-0002-5162-4417

Chi-Cuong Tran, National Taiwan University of Science and Technology, Taiwan

Chi-Cuong Tran received the B.S. and M.S. degrees in Automation and Control Engineering from Can Tho University, Vietnam, in 2015 and 2017, respectively. He received his Ph.D. degree in Mechanical Engineering from National Taiwan University of Science and Technology (NTUST), in 2023. He is currently working as a postdoctoral researcher at National Taiwan University of Science and Technology, Taipei, Taiwan. His research interests include intelligent robotics, intelligent automation, computer vision, and machine learning.

Email: tccuong09@gmail.com. ORCID:  https://orcid.org/0009-0004-7698-0970

The-Thinh Pham, Can Tho University of Technology, Vietnam

The-Thinh Pham received his Bachelor degree in Mechatronic Engineering from Can Tho University of Technology, Vietnam in 2019. He received his Master degree in Mechanical Engineering from National Taiwan University of Science and Technology, Taiwan in 2023. He is currently pursuing a Ph.D. degree with Mechanical Engineering, National Taiwan University of Science and Technology. His current research interests include computer vision, deep learning and robotics.

Email: ptthinh@ctuet.edu.vn. ORCID:  https://orcid.org/0009-0009-4426-0457

Duy-Tan Do, Ho Chi Minh University of Technology and Education, Vietnam

Duy-Tan Do received his B.S. degree from Ho Chi Minh City University of Technology (HCMUT), Vietnam, and M.S. degree from Kumoh National Institute of Technology, Korea, in 2010 and 2013, respectively. He received his Ph.D. degree from Autonomous University of Barcelona, Spain, in 2019. He is currently an Assistant Professor/Lecturer at the Department of Computer and Communication Engineering, Ho Chi Minh City University of Technology and Education (HCMUTE) in Vietnam. His main research interests include real-time optimization for resource allocation in wireless networks and coding applications for wireless communications.

Email: tandd@hcmute.edu.vn. ORCID:  https://orcid.org/0000-0003-4570-0441

Hoang-Vinh-Khang Nguyen, Vietnamese-German University, Vietnam

Hoang-Vinh-Khang Nguyen received his B.S. degree in Electrical Engineering and Information Technology (EEIT, now Electrical and Computer Engineering) from the Vietnamese-German University (VGU) in 2015 and his M.S. degree in Mechatronics and Sensor Systems Technology (MST) from VGU in 2018. As a recipient of the DAAD scholarship, he spent one year at Karlsruhe University of Applied Sciences, Germany, where he conducted research for his master's thesis. His research interests include biomedical signal processing for rehabilitation applications and exoskeleton robot control.

Email: khang.nhv@vgu.edu.vn. ORCID:  https://orcid.org/0000-0003-0256-2237

Quang-Chien Nguyen, Ho Chi Minh University of Technology and Education, Vietnam

Quang-Chien Nguyen received the B.S. degree in Automation and Control Engineering from Ho Chi Minh City University of Technology and Education (HCMUTE) in 2023. He is currently pursuing a Master's degree in Automation and Control Engineering at Ho Chi Minh City University of Technology and Education. His research interests include robotics, mobile robot, intelligent control and motion control.

Email: 2431101@student.hcmute.edu.vn. ORCID:  https://orcid.org/0009-0008-1332-7746

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Published

18-09-2025

How to Cite

Dong, Q.-H., Nguyen, T.-K., Tran, C.-C., Pham, T.-T., Do, D.-T., Nguyen, H.-V.-K., & Nguyen, Q.-C. (2025). Effectiveness of Digital Twin Framework for Collaborative Robotic Manipulation: VERSION OF RECORD ONLINE: 18/09/2025. Journal of Technical Education Science. https://doi.org/10.54644/jte.2025.1835