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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\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\({\\times}\\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            2 between-subjects study (\n            <jats:italic>N<\/jats:italic>\n            <jats:inline-formula content-type=\"math\/tex\">\n              <jats:tex-math notation=\"LaTeX\" version=\"MathJax\">\\({=}\\)<\/jats:tex-math>\n            <\/jats:inline-formula>\n            160), which evaluated the effect of the interaction environment (Real vs. Simulated environment) and participants\u2019 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\u2019 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\u2013robot 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.\n          <\/jats:p>","DOI":"10.1145\/3675784","type":"journal-article","created":{"date-parts":[[2024,7,16]],"date-time":"2024-07-16T11:43:21Z","timestamp":1721130201000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Influence of Simulation and Interactivity on Human Perceptions of a Robot During Navigation Tasks"],"prefix":"10.1145","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0823-4859","authenticated-orcid":false,"given":"Nathan","family":"Tsoi","sequence":"first","affiliation":[{"name":"Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9598-8204","authenticated-orcid":false,"given":"Rachel","family":"Sterneck","sequence":"additional","affiliation":[{"name":"Yale University, New Haven, CT, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0893-8920","authenticated-orcid":false,"given":"Xuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Stanford University, Stanford, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0698-5472","authenticated-orcid":false,"given":"Marynel","family":"V\u00e1zquez","sequence":"additional","affiliation":[{"name":"Yale University, New Haven, CT, USA"}]}],"member":"320","published-online":{"date-parts":[[2024,10,28]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12369-010-0082-7"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1177\/001872089203400408"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3434074.3447222"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3415139"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1017\/9781108676649"},{"issue":"10","key":"e_1_3_1_7_2","first-page":"11","article-title":"Interactivity: What is it and what can it do for computer-based instruction?","volume":"31","author":"Borsook Terry K.","year":"1991","unstructured":"Terry K. 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