Influence of Simulation and Interactivity on Human Perceptions of a Robot During Navigation Tasks

Dados Bibliográficos

ID22190874
AutoresNathan Tsoi (0000-0003-0823-4859, Yale University), Rachel Sterneck (0000-0002-9598-8204, Yale University), Xuan Zhao (0000-0002-0893-8920, Stanford University), Marynel Vázquez (0000-0003-0698-5472, Yale University)
Ano2024
Volume13
Fascículo4
Páginas1-19
Data de publicação2024-12-31
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoACM Transactions on Human-Robot Interaction (JOURNAL)
Identificadores do periódicoISSN: 2573-9522 • E-ISSN: 2573-9522
EditoraAssociation for Computing Machinery (ACM) (PUBLISHER)
DOI10.1145/3675784
OpenAlexW4400688490
IdiomaEN
Referências citadas44

In Human–Robot Interaction, researchers typically utilize in-person studies to collect subjective perceptions of a robot. In addition, videos of interactions and interactive simulations (where participants control an avatar that interacts with a robot in a virtual world) have been used to quickly collect human feedback at scale. How would human perceptions of robots compare between these methodologies? To investigate this question, we conducted a 2 \({\times}\) 2 between-subjects study ( N \({=}\) 160), which evaluated the effect of the interaction environment (Real vs. Simulated environment) and participants’ interactivity during human-robot encounters (Interactive participation vs. Video observations) on perceptions about a robot (competence, discomfort, social presentation, and social information processing) for the task of navigating in concert with people. We also studied participants’ workload across the experimental conditions. Our results revealed a significant difference in the perceptions of the robot between the real environment and the simulated environment. Furthermore, our results showed differences in human perceptions when people watched a video of an encounter versus taking part in the encounter. Finally, we found that simulated interactions and videos of the simulated encounter resulted in a higher workload than real-world encounters and videos thereof. Our results suggest that findings from video and simulation methodologies may not always translate to real-world human–robot interactions. In order to allow practitioners to leverage learnings from this study and future researchers to expand our knowledge in this area, we provide guidelines for weighing the tradeoffs between different methodologies

Human–computer interaction · Human–robot interaction · Interactivity · Multimedia · Perception · Robot · Simulation · Computer Science · Human-Automation Interaction and Safety · Psychology · Robotics and Automated Systems · Social Robot Interaction and HRI · Artificial Intelligence