# Digital Twin for Human-Robot Collaboration in Manufacturing: Review and Outlook
## 3 Review of DT in HRC
### Benefits of DT-HRC  
#### 3.5.1 Safety  
A critical challenge with DT-HRC is to develop a safe environment for the operators to work with the robots as well as to create a sense of trust in order to work together flexibly as a team [22; 34; 136; 137]. The literature which focuses on modelling the human aspect of HRC in DT is comparatively smaller than that which focuses on modelling the DT of the robot [17]. However, in recent years, modelling of the human aspect within the DT has become a more widely researched topic [100; 138; 139]. In HRC, the interpretation of human motion is challenging. Additionally, the dynamic nature of the shop floor increases the complexity associated with modelling of the collaborative environment [140]. A safe working environment for human operators is essential in HRC. This can be achieved by having feedback that gives an estimate of the approximate positions or the intentions of the operator by using machine learning and AI algorithms combined with non-invasive sensing methods [44; 46; 47; 140; 141; 142]. DT-HRC enables machine learning-based approaches to ensure safe HRC via simulation models without altering the physical environment [111]. In this regard, the cognitive symbiotic communication model has recently gained attention. There are a number of other techniques used in HRC for safety purposes. Methods such as voice, gesture, haptic and brainwave perceptions are applied to prevent human-robot collision and to carry out collaborative tasks efficiently [143]. For example, a force-based feedback system is used for the virtual verification of hand guidance control of a collaborative robot in automobile applications [144]. Similarly, vision sensors are widely used with HRC applications to monitor and track the operator and to lower the impact velocity [145]. Additionally, vision-based safety systems can assist in predicting human motion to effectively avoid a collision, optimize the trajectory of the robot, or alert the operator [146; 147]. Gesture-based control provides a safe method of interaction between the collaborative robot and the operator [148]. Here, the movement of the operator's arm is tracked to identify the commands from the operator to carry out tasks. Surface-pressure based standing posture recognition system combined with vision-based techniques and deep learning can be utilized to detect the operator's posture and predict the operator's intended action [149]. One advantage of DT-HRC is to effectively validate multiple techniques used in the collaborative scenario and to perform a risk assessment on the model so that the performance of the HRC is optimized before physical implementation on the shop floor. The safety standards formulated for the collaborative scenario determine various factors, such as the minimum safe distance between the human and the robot. The robots are required to take a safe route while working near the operator to ensure the safety of the operator [150]. A kinematic control strategy proposed focuses on the safety of the operator as well as ensuring maximum productivity [151]. Metrics, such as minimum separation distance used can be utilised to compare the results of the DT prototype and DT instances [151]. This strategy can help in optimising the trajectory of the robot so that the robot maintains a safe distance from the operator. Safety is considered one of the crucial aspects of HRC. As mentioned earlier, it is essential to develop a sense of trust between the human and the robot when tasks are carried out in a shared workspace [136; 137; 152]. However, the level of safety and trust in a collaborative environment is determined by the programmer who programs the robot. One challenge is the trade-off between robot velocity and safety in the HRC environment. This trade-off is illustrated in Figure 11. The higher the velocity of the robot, the quicker a task can be done, but this leads to lower trust and higher risk for the operator.