The rapid development of social robots has challenged robotics and cognitive sciences to understand humans' perception of the appearance of robots. In this study, robot-associated words spontaneously generated by humans were analyzed to semantically reveal the body image of 30 robots that have been developed over the past decades. The analyses took advantage of word affect scales and embedding vectors, and provided a series of evidence for links between human perception and body image. It was found that the valence and dominance of the body image reflected humans' attitude towards the general concept of robots; that the user bases and usages of the robots were among the primary factors influencing humans' impressions towards individual robots; and that there was a relationship between the robots' affects and semantic distances to the word ``person''. According to the results, building body image for robots was an effective paradigm to investigate which features were appreciated by people and what influenced people's feelings towards robots.
翻译:社会机器人的迅速发展使机器人和认知科学对理解人类对机器人外观的认知提出了挑战。在这项研究中,人类自发生成的机器人相关词被分析成从字面上揭示了过去几十年所开发的30个机器人的体形形象。分析利用了影响尺度和嵌入矢量的文字,为人类感知和身体形象之间的联系提供了一系列证据。发现身体形象的价值和主导性反映了人类对一般机器人概念的态度;机器人的用户基础和使用是影响人类对个体机器人印象的主要因素之一;机器人的影响与“人”一词的语义距离之间存在某种关系。根据分析结果,为机器人建立身体形象是一种有效的范例,可以调查哪些特征受到人们的赞赏,哪些影响人们对机器人的感觉。