The influence of matching between robots’ social cues on users’ social perceptions should be investigated systematically to better fit robots to their occupational roles. In this study, an experiment with 69 older and middle-aged participants was conducted to explore the effects of the voice and lighting color of a home healthcare robot on users’ social perception, which was measured by the Robotic Social Attributes Scale (RoSAS). The results indicated that voice and lighting color significantly affected social perceptions of the healthcare robot. Specifically, the adopted robot received high warmth ratings when it had an adult female voice or a child voice, whereas it received high competence ratings when it had an adult male voice. The robot received a high warmth rating and a high competence rating when warm and cool lighting were used, respectively, as visual feedback. Furthermore, a mismatch in the robot’s voice and lighting color was discovered to evoke feelings of discomfort. The findings of this study can be used as a reference to design robots with acceptable social perception and to expand the roles of social robots in the future.
Naked-eye-stereoscopic display is a human-machine complex system based on human being’s stereo vision, it shows parallax images on sub-screens and forms individual view zones to realize 3D vision. According to the optic mechanism , we use “Stereo Degree” to measure 3D optic parameter, then stereoscopic display vision character is described.
Since their development, social robots have been a popular topic of research, with numerous studies evaluating their functionality or task performance. In recent years, social robots have begun to be regarded as social actors at work, and their social attributes have been explored. Therefore, this study focused on four occupational fields (shopping reception, home companion, education, and security) where robots are widely used, exploring the influence of robot gestures on their perceived personality traits and comparing the gesture design guidelines required in specific occupational fields. The study was conducted in two stages. In the first stage, an interactive script was developed; moreover, observation was employed to derive gestures related to the discourse on the fields of interest. The second stage involved robot experimentation based on human–robot interaction through video. Results show that metaphoric gestures appeared less frequently than did deictic, iconic, or beat gestures. Robots’ perceived personality traits were categorized into sociality, competence, and status. Introducing all types of gestures helped enhance perceived sociality. The addition of deictic, and iconic gestures significantly improved perceived competence and perceived status. Regarding the shopping reception robot, after the inclusion of basic deictic and iconic gestures, sufficient beats gestures should be implemented to create a friendly and outgoing demeanor, thereby promoting user acceptance. In the home companion, education, and security contexts, the addition of beat gestures did not affect the overall acceptance level; the designs should instead be focused on the integration of the other gesture types.
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