Relieving operators' workload: Towards affective robotics in industrial scenarios

This paper proposes a novel approach based on affective robotics that can be applied to industrial applications. Considering a human-robot interaction task, we propose to analyze the mental workload of the operator, and subsequently adapt the behavior of the robotic system, introducing assistive technologies. These technologies would prevent the performances deterioration caused by the human stress, helping him/her only when needed and decreasing the user's mental workload. This represents a general methodology, which can be applied to several industrial applications, leading to increase the overall performances of human-robot interaction exploiting principles of human-centered design. As a case study, we consider a teleoperation task, where virtual fixtures are utilized as an assistive technology. The stress of the operator is monitored in terms of heart rate variability, measured by means of a wearable sensor tied at the operator's wrist. Experimental validation of the proposed architecture is performed on a group of 15 users that teleoperate an industrial robot for performing a pick and place task.