Within the context of the AD-HOC project, the interaction between humans and machines was evaluated within the Industry 4.0 framework, specifically focusing on collaborative robotics tools. The analysis encompassed both quantitative and qualitative evaluation techniques inherent to ergonomics and human-computer interaction.
The introduction of collaborative robots in the industry necessitates a human-centric perspective and consideration of a range of ergonomic criteria. The coexistence of individuals and robots aims to leverage the intelligence, creativity, and flexibility of humans, combined with the precision, strength, and tirelessness of robots in a working environment characterized by genuine sharing of spaces and tasks.

The support provided by cobots must be implemented on both physical levels (e.g., during strenuous tasks) and cognitive levels (e.g., mental overload/underload and fatigue in the case of complex or repetitive/monotonous tasks). During the experiments, various quantitative evaluation techniques and tools were employed, such as acceptance questionnaires, user experience assessments, and usability evaluations. Additionally, qualitative methods such as video analysis and semi-structured interviews were utilized. Cognitive and psychophysiological indices (e.g., blinks, heart rate frequency) were measured to detect conditions of cognitive overload, mental fatigue, and stress.

Research activities were conducted within companies to analyze the interaction and subjective perceptions of workers who interact with collaborative robots. Moreover, these activities facilitated an analysis of work tasks to identify which activities, within each business context (i.e., 3), could be assigned to the cobot’s action, which should remain within the domain of human operators, and which could benefit from a synergistic operator-cobot action.
Experiments were carried out using a prototype of a robotized workstation equipped with a collaborative robot, considering work tasks similar to those performed by operators in real-world contexts. Non-invasive wearable tools (e.g., eye-tracking glasses and surface sensors for cardiac activity) were employed for the detection of cognitive load and stress. Questionnaires and interviews were used to collect information, for example, on the acceptance and usability of a workstation equipped with a cobot.
Parameters (e.g., cognitive and psychophysiological factors) have been identified and operationalized into a model to enhance work activities, incorporating various possibilities for task allocation in the system’s design. This approach considers elements of productivity, quality, ergonomics, and cognitive effort, with the aim of maximizing benefits from both a productive and a human factor perspective.