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Despite the growing literature on human attitudes toward robots, particularly prosocial behavior, little is known about how robots' perspective-taking, the capacity to perceive and understand the world from other viewpoints, could infuence such attitudes and perceptions of the robot. To make robots and AI more autonomous and self-aware, more researchers have focused on developing cognitive skills such as perspective-taking and theory of mind in robots and AI. The present study investigated whether a robot's perspectivetaking choices could infuence the occurrence and extent of exhibiting prosocial behavior toward the robot.We designed an interaction consisting of a perspective-taking task, where we manipulated how the robot instructs the human to fnd objects by changing its frame of reference and measured the human's exhibition of prosocial behavior toward the robot. In a between-subject study (N=70), we compared the robot's egocentric and addressee-centric instructions against a control condition, where the robot's instructions were object-centric. Participants' prosocial behavior toward the robot was measured using a voluntary data collection session. Our results imply that the occurrence and extent of prosocial behavior toward the robot were signifcantly infuenced by the robot's visuospatial perspective-taking behavior. Furthermore, we observed, through questionnaire responses, that the robot's choice of perspectivetaking could potentially infuence the humans' perspective choices, were they to reciprocate the instructions to the robot., Part of ISBN 9781450399647QC 20230801

The evolving field of human-robot interaction (HRI) necessitates that we better understand how social robots operate and interact with humans. This scoping review provides an overview of about 300 research works focusing on the use of the NAO robot from 2010 to 2020. This study presents one of the most extensive and inclusive pieces of evidence on the deployment of the humanoid NAO robot and its global reach. Unlike most reviews, we provide both qualitative and quantitative results regarding how NAO is being used and what has been achieved so far. We analyzed a wide range of theoretical, empirical, and technical contributions that provide multidimensional insights, such as general trends in terms of application, the robot capabilities, its input and output modalities of communication, and the human-robot interaction experiments that featured NAO (e.g. number and roles of participants, design, and the length of interaction). Lastly, we derive from the review some research gaps in current state-of-the-art and provide suggestions for the design of the next generation of social robots.

Recent studies with children have pointed out the importance of spatial thinking as an essential factor in determining later success in STEM-related fields. The current study explores the potential of using embodied activities with robots to aid the development of children's spatial perspectivetaking abilities. This research focuses on evaluating children's spatial perspective-taking abilities and assessing the potential of the designed activity to practice perspective-taking. The activity design is inspired by the dynamic and mental processes involved in remote-controlled cars and racing games, it is developed with a Cozmo robot, and it includes guiding the robot within the maze by considering the robot's point of view. We evaluated the activity through a user study with 22 elementary school children between the ages of 8 and 9. The findings showed that children's performance at different angular disparities was aligned with the previous research in developmental psychology. Additionally, most children made fewer mistakes in guiding the robot as they played more. Finally, while we did not observe any performance improvement in the group of children who had access to the robot's point of view during the game, we learned new insights about how children perceived seeing the maze through the robot's eyes., QC 20221212Part of proceedings: ISBN 978-1-7281-8859-1

Spatial understanding and communication are essential skills in human interaction. An adequate understanding of others' spatial perspectives can increase the quality of the interaction, both perceptually and cognitively. In this paper, we take the first step towards understanding children's perspective-taking abilities and their tendency to adapt their perspective to a counterpart while completing a task with a robot. The elements used for studying children's behaviours are the frame of reference and perspective marking, which we evaluated through a task where players needed to compose instructions to guide each other to complete the task. We developed the interaction with an NAO robot and analyzed the children's instructions and their performance throughout the game. Our initial findings demonstrated that children tend to compose their first instruction by following the principle of least collaborative effort. Children significantly changed and adapted their perspective, i.e. frame of reference and perspective marking to the robot, mainly when the robot failed to follow their instructions correctly. Additionally, results show that children tend to create a mental model of their counterparts and the robot changing that frame of reference might affect their performance or the flow of the interaction., QC 20220913Part of proceedings: ISBN 978-145039197-9

Multisensory integration influences emotional perception, as the McGurk effect demonstrates for the communication between humans. Human physiology implicitly links the production of visual features with other modes like the audio channel: Face muscles responsible for a smiling face also stretch the vocal cords that result in a characteristic smiling voice. For artificial agents capable of multimodal expression, this linkage is modeled explicitly. In our studies, we observe the influence of visual and audio channels on the perception of the agents' emotional expression. We created videos of virtual characters and social robots either with matching or mismatching emotional expressions in the audio and visual channels. In two online studies, we measured the agents' perceived valence and arousal. Our results consistently lend support to the ‘emotional McGurk effect' hypothesis, according to which face transmits valence information, and voice transmits arousal. When dealing with dynamic virtual characters, visual information is enough to convey both valence and arousal, and thus audio expressivity need not be congruent. When dealing with robots with fixed facial expressions, however, both visual and audio information need to be present to convey the intended expression., QC 20230608

QC 20230503