## 1 Introduction
### Development Trajectory  
With continuous technological advancements, the application of industrial robots is also evolving to meet increasingly complex manufacturing demands and technical standards. The evolution of virtual-physical integration in industrial robot applications can be divided into four stages.  
1. Early Automation and Programming:  
From the 1960s to the 1970s, with the emergence and use of the first industrial robots, the focus was on basic automation technology and programming. During this period, all operational steps were performed in the real world, with the primary goal of enabling operators to understand and master the operation of the equipment. By the late 1970s to the 1980s, applications began to include microprocessor control and more flexible programming languages, such as VAL (Variable Assembly Language). At this stage, all operational steps were also completed in the real world.  
2. Integrated Systems and Enhanced Functions:  
In the 1990s, applications started focusing on the use of robots in integrated systems, involving enhanced functions such as vision recognition and intelligent sensing. During this development stage, the application of industrial robots began using offline data to recreate the actual working scenarios of robots in virtual environments [11]. Although the operation of robots in reality and virtual simulation was not synchronized in time, this method promoted the diversification and parameterized planning of applications [12]. Meanwhile, these virtual scenarios could be connected to real control systems, allowing for semi-physical simulation and debugging of the actual control systems, enhancing the interactivity and practicality of operations [13].  
3. Intelligent and Collaborative Robots:  
From the early 21 st century to the present, the focus has shifted to the intelligence and collaborative capabilities of industrial robots, emphasizing the integration of robot systems with AI and IoT technologies. At this stage, to overcome the inconsistency in time scales, the application of industrial robots has realized information-driven virtual scenarios that are synchronized with real systems in real time. Currently, [PERSON] et al. use Tecnomatix Plant Simulation(Tecnomatix/Siemens Product Lifecycle Management Software Inc.) to create a simulation model of a robotic arm system [14]; [PERSON] et al. use VRTS(HTC Vive Pro kit and Unity game engine) for virtual reality training with robots [15]; [PERSON] et al. use SOLIDWORKS for dual-arm modeling and simulation [16]; and [PERSON], [PERSON], and [PERSON] use Unity v2020.1 for the simulation of industrial robot working environments [17; 18]. Based on real-time, accurate virtual scenarios, parallel application systems synchronized with real-time status are constructed to simulate future planning and path selection [19]. During the simulation process of parallel systems, the optimal solution is selected and connected to the actual control system through information flow, and converted into control commands to guide the physical robots to execute tasks according to the optimal strategy.  
4. Industrial Metaverse Evolution:  
In the future, the industrial metaverse will be a new stage in the application of industrial robots. In this entirely virtual industrial environment, broader global collaboration and communication can be achieved, creating boundless operational and training scenarios, making production and operation geographically unrestricted, and greatly enhancing industrial efficiency and effectiveness [20]. [PERSON] et al. discussed enabling technologies (e.g., VR, DT, IIoT, etc.) to design a connection framework to achieve the purpose of the industrial metaverse [21]. The industrial metaverse will provide an immersive and interactive operational platform where users can perform real-time operational training and solve complex engineering problems through virtual collaboration, further promoting innovation and the application of industrial robot technology [22].