*2.2. Robot Simulators*

The first developments were orientated towards the simulation of the real robot or the real cell environment mainly for robot programming and operator training, but these first virtual environments were disconnected from the real movements. They were isolated tools provided by robot manufacturers which enabled one to foresee the manipulator behavior in a simulated environment. Each manufacturer provided its own solution for its robots; thus it was not possible to combine robots from different manufacturers. Moreover, as robotic languages are dependent on each manipulator, the simulation faces the same complexity as the real programming—one of the major hurdles still preventing automation using industrial robots [23]. Benchmarking of multi-robot systems is crucial for comparing the different existing solutions. However, there are only few and limited tools to support it. For instance, Yan in [14] presented a simulation tool based on a *robot operating system* (ROS).

Recently, these robot simulators have evolved by including new technologies, such as virtual and augmented reality, or new features, such as human–robot collaboration. The collaboration between humans and robots is necessary to increase industrial competitiveness, and the application of virtual and augmented reality is essential to enable a smoother collaboration with 3D immersive visualization [24]. Virtual reality (VR) offers a way to simulate reality. Originally, it was mainly used for entertainment purposes, but nowadays the evolution of the technologies, the appearance of multiple applications, and the reduction of costs have extended it to the manufacturing industry for a safer human–machine interaction [25]. Nowadays, several commercial simulation tools with

VR visualization are available, such as *Visual Components* [26], *Robotics and Automation* [27], and *RoboDK* [28]. These tools are also used for the virtual commissioning of a robotic cell, which involves creating a digital twin and then testing and verifying the model in a simulated virtual environment [20]. ROS is also combined with virtual reality to create human interfaces [29].

#### *2.3. Digital Twins and Robots*

Several works relate the use of digital twins with robots. Kousi in [30] used the digital twin to adapt a robot's behavior in assembly tasks of the automobile industry. Malik in [31] presented a digital twin framework to support human–robot collaboration. Ma in [32] proposed a digital twin for enhanced human–machine interaction. Bilberg in [33] also combined the digital twin with human–robot collaboration but added a task allocation. Aivaliotis in [34] applied the digital twin of a robot for predictive maintenance. In the literature, the digital twin concept is applied not only to the single robot but also to the whole manufacturing cell [35,36].

In order to train people in virtual reality with systems that behave realistically, there is the interesting option of combining virtual reality and digital twin technologies [11]. Burghardt in [37] and Kuts in [38] present different methods for programming and controlling robots using virtual reality and digital twins, confirming that this combination facilitates human–robot interactions in terms of collaborative work, telecontrol, and programming.
