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

Against the background of the uncanny valley hypothesis (Mod, 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 Mod, but rather by linear or quadratic relationships. (C) 2014 Elsevier Ltd. All rights reserved.