Unlike humanoid robots, articulated robots cannot interact with humans using human characteristics such as voice, gaze, or faces. As compared to humanoid robots articulated robots therefore possess a small range of options for interacting with humans and gain their trust.
In our research, we therefore investigate how articulated robot arms needs to behave to increase worker acceptance, based exclusively on their movement behavior.
Our findings demonstrate that by modulating certain movement parameters, human perception and acceptance can be influenced, even without users explicitly noticing. To measure the effect of different robot behaviors, we not only use self-reported responses, but also physiological and behavioral responses such as heart rate, pupil dilation, proxemics, and how they relate to static individual differences like gender, age or prior experience with robots.
