How design characteristics of robots determine evaluation and uncanny valley related responses

Against the background of the uncanny valley hypothesis (Mori, 1970) and its conceptual shortcomings the present study aims at identifying design characteristics which determine the evaluation of robots. We conducted a web-based survey (N = 151) with standardized pictures of 40 robots which were evaluated. A cluster analysis revealed six clusters of robots. We were able to identify different groups of robots which were rated significantly different on six dimensions. Interestingly, in two clusters robots were rated both low in human-likeness and low in ''mechanical'' indicating that in future research these adjectives should be used separately. The robots in those clusters with a high mean concerning ''Threatening'' are almost all bi-pedal robots. In contrast to the humanoid robots (cluster 5), the android robots (clusters 3 and 4) were rated higher on ''Familiarity'', and on ''Likability'' although all three clusters (3, 4, and 5) were rated as ''Threatening'' which contrasts the uncanny valley hypothesis. Moreover, the data in the present study could not be explained by a cubic function as would be suggested by the graph proposed by Mori, but rather by linear or quadratic relationships. Since Masahiro Mori introduced his theory of the uncanny valley in 1970 the uncanny valley is widely considered as a design obstacle to overcome. Mori started with the observation that people tend to describe the relationship between any given two variables as monotonically increasing (i.e. linear) function and that people would react with confusion when they encountered a phenomenon which cannot be explained by this function. He stated that he observed something similar in the field of robotics with regard to people's affinity towards robots: ''I have noticed that, in climbing toward the goal of making robots appear human, our affinity for them increases until we come to a valley, which I call the uncanny valley'' (Mori, MacDorman, & Kageki, 2012). The model states that the more human-like robots become the more our affinity for these robots increases and we are more willing to accept them (cf. Fig. 1). However, shortly before the ideal of perfect humanness is reached the curve dips and affinity reverses into uncanniness. Mori described this effect for still as well as for moving objects, although the effect is more pronounced when movement is involved (cf. Fig. 2). A number of explanations for the uncanny valley effect have been proposed. Some explanations address the level of perception and direct cognition (violation …