首页|New Androids Data Have Been Reported by Researchers at University of Florence (F rom the Definition To the Automatic Assessment of Engagement In Human-robot Inte raction: a Systematic Review)
New Androids Data Have Been Reported by Researchers at University of Florence (F rom the Definition To the Automatic Assessment of Engagement In Human-robot Inte raction: a Systematic Review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Robotics - Androids h ave been presented. According to news reporting originating from Florence, Italy , by NewsRx correspondents, research stated, “The concept of engagement is widel y adopted in the human-robot interaction (HRI) field, as a core social phenomeno n in the interaction. Despite the wide usage of the term, the meaning of this co ncept is still characterized by great vagueness.” Financial support for this research came from Ministero dell’Universit e della R icerca. Our news editors obtained a quote from the research from the University of Flore nce, “A common approach is to evaluate it through self-reports and observational grids. While the former solution suffers from a time-discrepancy problem, since the perceived engagement is evaluated at the end of the interaction, the latter solution may be affected by the subjectivity of the observers. From the perspec tive of developing socially intelligent robots that autonomously adapt their beh aviors during the interaction, replicating the ability to properly detect engage ment represents a challenge in the social robotics community. This systematic re view investigates the conceptualization of engagement, starting with the works t hat attempted to automatically detect it in interactions involving robots and re al users (i.e., online surveys are excluded). The goal is to describe the most w orthwhile research efforts and to outline the commonly adopted definitions (whic h define the authors’ perspective on the topic) and their connection with the me thodology used for the assessment (if any). The research was conducted within tw o databases (Web of Science and Scopus) between November 2009 and January 2023. A total of 590 articles were found in the initial search. Thanks to an accurate definition of the exclusion criteria, the most relevant papers on automatic enga gement detection and assessment in HRI were identified. Finally, 28 papers were fully evaluated and included in this review. The analysis illustrates that the e ngagement detection task is mostly addressed as a binary or multi-class classifi cation problem, considering user behavioral cues and context-based features extr acted from recorded data.”
FlorenceItalyEuropeAndroidsEmerg ing TechnologiesHuman-Robot InteractionMachine LearningNano-robotRobotRoboticsUniversity of Florence
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