# On Cognitive Assistant Robots for Reducing Variability in Industrial Human-Robot Activities
## 2 Performance of Human-Robot Systems
### State of the Art
\begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Approach** & **Category** & **Metrics** & **Features** \\ \hline \multirow{2}{*}{Research [15]} & \multirow{2}{*}{Cognitive} & H,R task effectiveness, Interaction effort, Situational awareness & Review and Classification of common metrics \\ \hline \multirow{2}{*}{Research [17]} & Physical and Cognitive & \multirow{2}{*}{Human-robot teaming performance} & \multirow{2}{*}{Developing a metrology suite} \\ \cline{3-3} \cline{5-5}  & & & \\ \hline \multirow{2}{*}{Research [18]} & \multirow{2}{*}{Physical} & Subjective metrics in a 7-point Likert scale survey (seven heuristics) & Physical human interaction is modelled as informative and not as a disturbance \\ \hline \multirow{2}{*}{Research [19]} & \multirow{2}{*}{Cognitive} & Physiological, Task analysis & Model and comparison of H-H team, H-R team \\ \hline \multirow{2}{*}{Research [20]} & \multirow{2}{*}{Cognitive} & Fluency & H-R teams research \\ \hline \multirow{2}{*}{Social [21]} & \multirow{2}{*}{Cognitive} & System Usability Scale (SUS) questionnaire & Early detection neurological impairments such as dementia \\ \hline \multirow{2}{*}{Social [22]} & \multirow{2}{*}{Cognitive} & Task effectiveness & H-R model with perception, knowledge, plan and action \\ \hline \multirow{2}{*}{Industry [23]} & \multirow{2}{*}{Physical} & Human localization, Latency, Performance & Prediction of future locations of H,R for safety \\ \hline \multirow{2}{*}{Industry [24]} & \multirow{2}{*}{Physical} & Completion task time & Robotic assembly systems \\ \hline \multirow{2}{*}{Industry [25]} & \multirow{2}{*}{Physical} & H-R distance, speed, performance; Time collision & Algorithm case studies, Standards ISO 13855, ISO TS 15066 \\ \hline \multirow{2}{*}{Industry [26]} & \multirow{2}{*}{Physical} & H-R risk, Degree of collaboration, Task analysis & Assembly line with H-R shared tasks \\ \hline \multirow{2}{*}{Industry [27]} & \multirow{2}{*}{Physical and Cognitive} & Level of Collaboration; H,R fully controlled, cooperation & H holistic perspective in human-robot cooperation \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A comparison among several Human-Robot Interaction metrics. Columns show the robotics approach, the interaction level, the employed metrics and some particular features. \(H\), \(R\) notation means human or robot (traded), while \(H\)-\(R\) means human and robot (shared). that operators change their working behaviors. For instance, the not so noticeable fatigue is mental fatigue. By applying sensors for measuring heart rate or respiratory rate, for example, it is possible to collect data on the state of the human and recommend breaks. Some authors focus their research in the direction of an intuitive human-robot interaction taking into account human cognitive skills. For instance, speed control of a mobile robot [28], or in communication with a collaborative robot [29]. In both cases, brain computer interfaces (BCI) are used to achieve a good accuracy and improve the feedback answer between human and robot for an effective performance. All this sensory devices can become invasive, and traditionally a questionnaire is used when the task is finished, to collect the subjective assessment of the operator. The NASA-TLX questionnaire measures mental load and is suitable for assessing differences in cognitive load when the human is carrying out a main task and a secondary task is added [15; 19]. Thus, an improved workplace setting should take into account the joint framework conformed by human, cognitive agent, and collaborative robot. In this context, we should distinguish two roles for the human: _supervisor_ and _operator_. In the case of a human with the role of supervisor, the cognitive agent assists her/him in deciding the best task planning. The cognitive robot can show the performance of the set of operators that work with collaborative robots and can provide guidelines for a better assignment of tasks to operators.