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Body Language for Personal Robot Arm Assistant

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-grou...

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Bibliographic Details
Published in:International journal of social robotics 2022, Vol.14 (1), p.15-37
Main Authors: Chatterjee, Sridatta, Parmet, Yisrael, Oron-Gilad, Tal
Format: Article
Language:English
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Summary: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.
ISSN:1875-4791
1875-4805
DOI:10.1007/s12369-021-00748-y