MINISTRY OF EDUCATION AND TRAINING HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY Doan Thanh Xuan RESEARCH ON DEVELOPING DIGITAL TWINS- BASED APPLICATION FOR INDUSTRIAL ROBOTS Major: Mechanical Engineering Code: 9520103 DOCTORAL DISSERTATION IN MECHANICAL ENGINEERING Hanoi - 2024 MINISTRY OF EDUCATION AND TRAINING HANOI UNIVERSITY OF SCIENCE AND TECHNOLOGY Doan Thanh Xuan RESEARCH ON DEVELOPING DIGITAL TWINS- BASED APPLICATION FOR INDUSTRIAL ROBOTS Major: Mechanical Engineering Code: 9520103 DOCTORAL DISSERTATION IN MECHANICAL ENGINEERING SUPERVISORS: Prof. Vu Toan Thang Assoc. Nguyen Thanh Hung Hanoi - 2024 GUARANTEE I hereby confirm that this is my own scientific research work. The contents and data used for analysis in the dissertation have clear sources and have been published in accordance with regulations.
The research results in the dissertation were independently researched and analyzed by me in an honest, objective, and suitable manner for the conditions in Vietnam. These results have not been published by any other author in any other research. Hanoi, 23rd January 2024 Science instructor Postgraduate Prof. Vu Toan Thang Doan Thanh Xuan Assoc.
Nguyen Thanh Hung ACKNOWLEDGMENT When completing this dissertation, I received dedicated guidance from the academic advisors, the support of the Training Department, and School of Mechanical Engineering at the Hanoi University of Science and Technology. Additionally, the Robotics Group and the Department of Mechatronics at the Hanoi University of Science and Technology offered the necessary conditions for my research. To facilitate my research, I had the opportunity to work in the Laboratory of Smart Digital Factory at the School of Mechanical Engineering - Hanoi University of Science and Technology, which allowed me to conduct measurements and experiments related to the UR3 robot in the lightbulb assembly system. The leaders of the School of Mechanical Engineering, the Department of Mechatronics, and the Robotics Group at the Hanoi University of Science and Technology have provided me with the necessary conditions for my scientific research, assisting me in accessing the equipment required for experiments related to the topic of my research.
I received valuable contributions and advice from professors, associate professors, doctors, and colleagues, who also provided relevant materials related to the topic of my research. Moreover, I obtained support and encouragement from the graduate students at the School of Mechanical Engineering during the process of completing the procedures and the content of my PhD dissertation. I want to express my heartfelt gratitude to all the individuals and groups, who provided me with guidance, assistance, and resources throughout this journey. I especially want to thank my dissertation supervisors, Prof.
Vu Toan Thang and Assoc. Nguyen Thanh Hung, for their invaluable support. I would also like to extend my thanks to my colleagues, friends, and family for their encouragement, sharing, and creating favorable conditions during my research. Sincerely, Doan Thanh Xuan TABLE OF CONTENT LIST OF ABBREVIATIONS AND ACRONYMS.
5 LIST OF FIGURES. 6 LIST OF TABLES. The Reasons for Choosing The Dissertation Topic. Goal, Objectives, Scope, and Research Methodology.
The Scientific and Practical Significance of the Research Topic. The new findings. 11 Chapter 1: OVERVIEW OF DIGITIAL TWINS AND THEIR APPLICATIONS. The History of Digital Twin Development and Milestones.
The History of Development. Key Milestones in the Development of Digital Twin Technology. Digital twin concept and classification. Digital twin concept.
Integration-based classification of digital twins. Technologies associated to digital twin. Digital twin application. Digital twin application for robotic path planning.
Digital twin application for human-robot collaboration. The research status both domestically and internationally. International research status. National research status.
Conclusion of Chapter 1. 28 Chapter 2: DEVELOPING A DIGITAL TWIN FOR THE INDUSTRIAL ROBOT IN THE LIGHTBULB ASSEMBLY SYSTEM. Lightbulb assembly system. Kinematic calculations and development of digital twin for the UR3 robot.
Kinematic calculations of the UR3 robot. Modelling the UR3 robot. Conclusion of Chapter 2. 52 Chapter 3: APPLICATION OF DIGITAL TWINS IN PATH FINDING FOR ROBOTS.
Robot path planning problem .1 Path planning problem for robot. End-effector motion of the robot. The A* pathfinding algorithm. The A* pathfinding algorithm.
The improved A* algorithm. Application combining digital twins and A* algorithm in robot pathfinding 62 3. Application of combining the digital twin and improved A* algorithm in robot pathfinding problem. Using the digital twin method.
Using the A* algorithm. Adding obstacles with the same height .4 Adding obstacles with varying heights .5 Conclusion of Chapter 3. 77 Chapter 4: APPLICATION OF DIGITAL TWINS IN HUMAN-ROBOT COLLABORATION. Collaboration between humans and robots.
Applying a combination of the digital twin method and genetic algorithm in the problem of human-robot collaboration. Overall framework diagram of the digital twin method for human-robot collaboration. Description of the human-robot collaboration system. Application of digital twins in human-robot collaboration.
Application of genetic algorithms in human-robot collaboration. Initialization of the initial population. Objective evaluation function. Results and discussion .3 Conclusion of Chapter 4.
102 FUTURE RESEARCH DIRECTIONS. 104 LIST OF PUBLICATIONS. 111 LIST OF ABBREVIATIONS AND ACRONYMS No. Short form Full form 1 BMI Body Mass Index 2 CAD Computer Aided Design 3 DE Differential Evolution 4 DH Denavit-Hartenberg 5 DT Digital Twin 6 EDT Experimentable Digital Twins 7 ERP Enterprise Resource Planning 8 GA Genetic Algorithm 9 HRC Human-Robot Cooperation 10 ICT Information & Communications Technology 11 ISO International Organization for Standardization 12 JT Jupiter Tessellation 13 MGA Multi-Adaptive Genetic Algorithm 14 MQTT Message Queueing Telemetry Transport 15 NASA National Aeronautics and Space Administration 16 OPC-UA Open Platform Communications-Unified Architecture 17 PLC Programmable Logic Controller 18 PLM Product Lifecycle Management 19 PSO Particle Swam Optimization 20 SRC Source 21 TCP/IP Transmission Control Protocol/Internet Protocol 22 UR Universal Robot Page 5 LIST OF FIGURES Figure 1.
1 Key Milestones in the development of digital twin technology. 2 Digital twin framework for production. 3 Classification of digital twins based on the degree of integration. 2 Robot algorithm flowchart.
3 Algorithm flowchart for supplying lightbulb caps, sockets and completing lightbulb assembly. 4 Algorithm flowchart for product return cycle. 5 UR3, UR5 and UR10 industrial robot product line. 6 Kinematic parameters of the UR3.
7 Motion model of the UR robot. 8 The angle limits and joint speeds of the UR3 robot's joints. 9 Vertical Projection (Left) and Side Projection (Right) of the workspace of the UR3 robot. 10 Steps for building a digital model of the UR3 robot.
11 A digital model of the lightbulb assembly system created by Tecnomatix Process Simulate software. 12 Real time connection between a real robot and a virtual robot. 1 Target position and trajectory. 2 Tool Center Point (TCP) of the gripper.
3 Comparison of toolpath with and without TCP. 4 Base coordinate system and coordinate system attached to the tool. 5 The flowchart of the A* algorithm. 6 The flowchart of the improved A* algorithm.
7 A simple example of a robot task. 8 A* algorithm-based path planning. 9 Optimal result of the first step on the left, the second step on the right. 10 The optimal result of the final step.
11 An actual image of the complete lightbulb assembly system. 12 A sequence of tasks in the lightbulb assembly system. 13 Collision detection in Tecnomatix software. 14 A visual depiction of the robotic path using Python programming.
15 Coordinates of the motion points along the robot's path determined through the implementation of the A* algorithm in Python. 16 Robotic path found by the digital twin method. 17 Robotic path found by the original A* algorithm (the left) and by the improved A* algorithm (the right). 18 Robotic path found by the improved A* algorithm when a 30-mm obstacle added.
19 Robotic path found by the improved A* algorithm when a 50-mm obstacle added. 20 Real image of the pairs of obstacles. 21 Representation of the pairs of obstacles. 1 Genetic algorithm diagram.
2 A chart illustrating the Roulette selection method. 3 Overall framework diagram of the digital twin method for human-robot collaboration. 4 Real image (on the left) and schematic diagram (on the right) of the miniature lightbulb assembly system. 5 The real human and robot (displayed on the left) and their digital representations within Tecnomatix software (featured on the right).
7 The crossover operation of two chromosomes. 8 The chart illustrates the best fitness indices of a population across each generation. 9 The chart comparing Eb, Es, and M across generations. 10 The chart displaying entropy across generations.
11 The best working process can be obtained in the form of encoding. 12 The graph of the best_fitness value across generations. 13 The graph of the mean_fitness value across generations. 100 LIST OF TABLES Table 1.
1 Definitions of digital twins in studies from 2019 and earlier. 2 Technologies and tools for DT. 1 D-H parameter table of the UR3 robot on the lightbulb assembly table 33 Table 2. 2 Analytical solutions of the inverse dynamics problem.
1 Coordinate parameters (A) and durations (B) for robotic movement in the phase devoid of large-sized obstacles. 2 Robotic movement times before and after the A* algorithm applied. 3 Coordinate parameters (A) and durations (B) for robotic movement according to AA1F1F. 4 Coordinate parameters (A) and durations (B) for robotic movement according to ABCDEF.
5 Coordinate parameters (A) and durations (B) for robotic movement according to ACDF. 6 Coordinate parameters (A) and durations (B) for robotic movement according to ACD1F. 7 Coordinate parameters (A) and durations (B) for robotic movement according to ACD2F. 8 Coordinate parameters (A) and durations (B) for robotic movement when more pairs of obstacles added in a 50-mm decreasing order of height.
1 Gene encoding on chromosomes. The Reasons for Choosing The Dissertation Topic Simulating a process or a system helps humans gain a deeper understanding of the system, allowing for flexibility to adjust and change device parameters as well as to perform optimization testing during the initial planning phase. Due to the advantages mentioned above, simulation has been widely researched and applied. However, it has mostly been limited to static models and one-way information exchange from physical objects to digital entities.
The concept of the digital twin, aiming to create a digital counterpart that faithfully describes a physical device and can exchange data with it, has been gaining increasing attention from researchers. Along with the strong development of digital technology and new-generation information, the ability to collect more data and process it efficiently has provided a strong foundation for the development of digital twins. The digital factory has become an inevitable trend in various industries, with the digital twin being a fundamental unit; synthesizing digital twins forms a digital factory. Research on building digital twins for robots is a relatively new field, meeting practical industrial demands and promising strong development prospects in the coming years, both domestically and internationally.
This research is based on theoretical studies and experiments to construct a digital model that faithfully describes a robot and establishes communication connections between the physical entity and the digital model. The experiments are conducted on the UR3 robot within a lightbulb assembly system. The digital twin of the UR3 robot, once created, continues to be applied in tasks such as pathfinding and optimizing collaboration between humans and robots. The application of robots is becoming increasingly popular, in line with the development of the automation industry.
Current research in robotics continues to grow due to high market demand, a wide range of applications, and technical development potential. Particularly, robot path planning has been extensively studied and applied across various generations of algorithms.