## 3 State of the Art
### Additional Human State Measuring Techniques for Collaborative Robotics
Immersive Technologies as a Safe Training Ground for Reinforcement Learning in Human-Interactive Robotics  
Given the direct interaction between robots and humans in the field of robotics, which often poses risks, assessing the practicality of virtual reality in experiments related to collaborative robotics is essential. This section seeks to differentiate among virtual reality, mixed reality, and augmented reality to analyze their potential application in future research projects. Virtual reality refers to a computer-generated environment that immerses the user in a simulated reality, often using a headset or other sensory input devices [67]. In VR, users can interact with and experience a digitally created world that can be entirely different from the physical world [68; 69]. Augmented reality (AR) overlays digital information or virtual elements onto the real-world environment [70]. AR enhances the user's perception of the physical world by providing additional digital content or information, often through a mobile device's camera or specialized glasses [71; 72]. Mixed reality (MR) combines elements of both virtual reality and augmented reality. In MR, digital objects or information are integrated into the real world in a way that allows them to interact with physical objects and the user's environment [73]. In the field of augmented reality and collaborative robotics, a novel solution was proposed, involving a human-robot collaboration method using augmented reality to enhance construction waste sorting, aiming to improve both efficiency and safety [74]. Mixed reality is also becoming more popular due to some recently released products and some interesting research, ensuring the possibility of applying mixed reality in robotic environments to enhance the interactions between humans and robots [75]. Virtual reality is widely used to simulate real environments, aiming to prevent harm to humans and train users for specific tasks. It is especially prevalent in the medical field, where virtual reality trains medical students to perform complex surgeries [76]. Additionally, this technology can be used to learn how to interact with robots in medical settings or other environments [77]. The intersection between virtual reality and human interaction is also a hot topic. A system that combines robotics with virtual reality to improve welding by interpreting the welder's intentions for robotic execution was recently introduced. Utilizing virtual reality for intention recognition enables precise and smooth robotic welding. This highlights the potential of integrating robotics and virtual reality in skilled tasks [78]. On the other hand, in order to apply reinforcement learning to train a robotic system to take into account different emotions or states of a human beings, the ideal solution is virtual reality, as these environments meet the safety requirements to guarantee humans are not harmed during experimentation. A recent study [79] describes a method where the virtual reality environment adapts to participant behavior in real time through reinforcement learning, focusing on encouraging helping behavior towards a victim in a simulated scenario of a violent assault. If robotic training has already been carried out, virtual reality is also a reliable validation technique to test the performance of the system in real-life environments, complying with the required safety conditions. Thanks to the virtual reality glasses that are on the market these days, environments can be generated in a very simple way. One of the examples in which this type of technology can be useful is when interacting with a factory or robotic facility, where the moving parts that can endanger human safety are simulated by the devices [35; 80]. In several studies presented in previous sections that implemented virtual reality to provide a safe environment for experimentation, it became clear that the results are very similar to those obtainable in a real environment.