Enhancing social responses: effects of controlling language by a social robot in a decision-making game for human-robot interaction (HRI)

• Հիմնական հեղինակներ: Rosli, Muhammad Azeem, Ghazali, Aimi Shazwani, Shamsul Bahrin, Muhammad Ikmal Hakim
• Ձևաչափ: UMS Journal (OJS)
• Լեզու: eng
• Հրապարակվել է: Universitas Muhammadiyah Surakarta 2022
• Խորագրեր: Decision-making game; Galvanic skin response (GSR); Human-robot interaction (HRI); Psychological reactance; Wizard of oz (WoZ)
• Առցանց հասանելիություն: https://journals2.ums.ac.id/index.php/arstech/article/view/1187
• Ամփոփում: The rise of technology has induced the development of robots that engage with humans through social interaction. The robot is believed to be capable of assisting humans in their life. However, the current technology is still far from a fully autonomous robot as there are many limitations. Additionally, it is unclear whether the current social robot effectively influences social reactance in Human-Robot Interaction (HRI). The study's objective is to investigate the influence of social cues used by the social robot on human social responses for HRI applications. Also, the study validates the reactance scale used in the questionnaire by correlating the measure with Galvanic Skin Response (GSR) readings. The study proposes a Wizard of Oz (WoZ) approach to observe HRI through decision-making games. A social robot is programmed to persuade participants to make choices. The participants' decisions made during the experiment and their GSR reading are recorded, and then they are asked to answer questionnaires. Statistical analyses are done on the collected data using the regression and MANOVA statistical tests. As a result, there is a significant correlation between GSR reading and enjoyment. Regarding social cues, the participants feel more relaxed when the social robot exhibits social cues in High Controlling Language (HCL) conditions rather than Low Controlling Language (LCL) conditions. Furthermore, the Attitude trait of the social robots greatly influences human perceived social intelligence towards the robot.