This article presents an exploratory study aimed at: (i) understanding participants’ first impression of the Cyton Gamma 1500, a small machine-like robot arm, and (ii) designing robot body language to convey certain intentions with regard to a personal assistant robotic application. The between-group study comprised of three distinct groups of participants. Each group had a different first encounter with the robot arm: the first group saw an idly sitting robot arm; the second group watched another person working with the robot; lastly, the third group worked with the robot themselves. They rated the robot arm on a bipolar adjective questionnaire after the first encounter which gives us insights into participant’s “first impression”. Then they performed a categorization task where they chose the most suitable posture for conveying specific messages. The objective here was to select postures that can easily convey the robot assistant’s intentions to users in future. The two main findings of the study are: (1) participants’ impression of the robot arm does not differ significantly across the three groups despite having different “first encounter” with the robot, and (2) certain postures are easily relatable to the message they convey (like, Robot is saying “Hi!”), while certain others are not (like, Robot has surrendered). In light of phenomenological theories of communication, it was concluded that tempered forms of anthropomorphic or zoomorphic postures are more easily identified than completely abstract postures. The findings of this study can be used to design robot-specific body language for robot arms.

本文提出了一项探索性研究，旨在：（i）了解参与者对Cyton Gamma 1500（一种类似机器的小型机械臂）的第一印象，以及（ii）设计机器人的肢体语言来传达有关个人助理机器人的某些意图应用。组间研究由三个不同的参与者组组成。每个小组对机器人手臂的第一次接触都不相同：第一小组看到一个闲坐的机器人手臂。第二组看着另一个人在用机器人工作；最后，第三组与机器人一起工作。第一次接触后，他们在双极形容词问卷中对机械臂进行了评分，这使我们对参与者的“第一印象”有了深刻的了解。然后，他们执行了分类任务，在此任务中，他们选择了最适合的姿势来传达特定的消息。目的是选择将来可以轻松将机器人助手的意图传达给用户的姿势。该研究的两个主要发现是：（1）尽管与机器人有不同的“初次相遇”，但三组参与者对机器人手臂的印象并没有显着差异；（2）某些姿势很容易与信息相关他们传达了信息（例如，机器人说“嗨！”），而另一些人则没有（例如，机器人投降了）。根据传播的现象学理论，得出的结论是，与完全抽象的姿势相比，拟人化或人为化姿势的钢化形式更容易识别。这项研究的结果可用于设计机器人手臂的机器人特定肢体语言。