An experimental focus on learning effect and interaction quality in human–robot collaboration

In the landscape of the emerging Industry 5.0, human–robot collaboration (HRC) represents a solution to increase the fex ibility and reconfgurability of production processes. Unlike classical industrial automation, in HRC it is possible to have direct interaction between humans and robots. Consequently, in order to efectively implement HRC it is necessary to con sider not only technical aspects related to the robot but also human aspects. The focus of this paper is to expand on previous results investigating how the learning process (i.e., the experience gained through the interaction) afects the user experience in the HRC in conjunction with diferent confguration factors (i.e., robot speed, task execution control, and proximity to robot workspace). Participants performed an assembly task in 12 diferent confgurations and provided feedback on their experience. In addition to perceived interaction quality, self-reported afective state and stress-related physiological indica tors (i.e., average skin conductance response and heart rate variability) were collected. A deep quantitative analysis of the response variables revealed a signifcant infuence of the learning process in the user experience. In addition, the perception of some confguration factors changed during the experiment. Finally, a signifcant infuence of participant characteristics also emerged, auguring the necessity of promoting a human-centered HRC.