Browsing by Subject "Social robotics"

Now showing 1 - 4 of 4

Open Access
A naturalistic laboratory setup for real-world HRI studies
(Association for Computing Machinery, 2024-03-11) Pekçetin, T.N.; Evsen, Şeyda; Pekçetin, S.; Karaduman, Tuvana Dilan; Acarturk, C.; Ürgen, Burcu Ayşen
We present our novel naturalistic laboratory setup that facilitates the presentation of real-world live-action stimuli by physically present actors in a controlled manner. Participants observe liveaction stimuli through a screen, which is surrounded by curtains, akin to a theatre experience, and promptly evaluate them when the screen turns to its opaque mode. Additionally, we introduce key components of the setup, including curtains, an actor PC, a security camera, and a bell, and the insights we gained during the task development. This innovative setup holds promise for advancing real-world investigations in Human-Robot Interaction.
Open Access
Investigating mind perception in HRI through real-time implicit and explicit measurements
(Association for Computing Machinery, 2024-03-11) Pekçetin, T.N.; Acarturk, C.; Ürgen, Burcu Ayşen
Social robots have revolutionized social interaction and communication. Thisstudy explores our perception of robots, focusing on the factors infuencing evaluations of Agency and Experience - two dimensions of mind perception. Three distinct aspects of our research include: investigating perceiver determinants alongside perceived agents and their actions, utilizing a naturalistic setup featuring live actions of both human and robot actors, and employing a comprehensive approach with both implicit and explicit measurements. In-person data were collected from 160 individuals across four generations. Future steps involve data analysis and result discussion. This study reevaluates the determinants of mind perception using a real-time paradigm, intending to contribute to the ongoing debate and deepen our understanding of mind perception in HRI.
Open Access
Real-world implicit association task for studying mind perception: insights for social robotics
(Association for Computing Machinery, 2024-03-11) Pekçetin, T.N.; Evsen, Şeyda; Pekçetin, S.; Acarturk, C.; Ürgen, Burcu Ayşen
In response to the growing demand for enhanced integration of implicit measurements in Human-Robot Interaction (HRI) research, the need for studies involving physically present robots, and the calls for a transition from lab experiments to more naturalistic investigations, we introduce the Real-World Implicit Association Task (RW-IAT). This report outlines the versatile methodology of the RW-IAT; emphasizing its allowance to present real-life stimuli and capture behavioral data, including response times and mouse tracking metrics in a controlled manner. Sample analyses focusing on communicative and noncommunicative actions between a human actor and the Pepper robot reveal signifcant efects on the Agency and Experience dimensions of the mind perception. We believe the methodology we proposed will contribute to conducting ecologically valid research in the feld of HRI in real-world contexts.
Open Access
Studying mind perception in social robotics ımplicitly: the need for validation and norming
(Association for Computing Machinery, 2023-03-13) Pekçetin, T. N.; Barinal, Badel; Tunç, J.; Acartürk, C.; Ürgen, Burcu Ayşen
The recent shift towards incorporating implicit measurements into the mind perception studies in social robotics has come along with its promises and challenges. The implicit tasks can go beyond the limited scope of the explicit tasks and increase the robustness of empirical investigations in human-robot interaction (HRI). However, designing valid and reliable implicit tasks requires norming and validating all stimuli to ensure no confounding factors interfere with the experimental manipulations. We conducted a lexical norming study to systematically explore the concepts suitable for an implicit task that measures mind perception induced by social robots. Two-hundred seventy-four participants rated an expanded and strictly selected list of forty mental capacities in two categories: Agency and Experience, and in two levels of capacities: High and Low. We used the partitioning around medoids algorithm as an objective way of revealing the clusters. We discussed the different clustering solutions in light of the previous findings. We consulted on frequency-based natural language processing (NLP) on the answers to the open-ended questions. The NLP analyses verified the significance of clear instructions and the presence of some common conceptualizations across dimensions. We proposed a systematic approach that encourages validation and norming studies, which will further improve the reliability and reproducibility of HRI studies.