Social Signal Modeling in Human-Robot Interaction

被引:1
作者
Stiber, Maia [1 ]
Spitale, Micol [2 ]
Gunes, Hatice [3 ]
Huang, Chien-Ming [1 ]
机构
[1] Johns Hopkins Univ, Baltimore, MD 21218 USA
[2] Politecn Milan, Milan, Italy
[3] Univ Cambridge, Cambridge, England
来源
COMPANION OF THE 2024 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION, HRI 2024 COMPANION | 2024年
基金
美国国家科学基金会;
关键词
Social Signals; Human Behavior Modeling; HRI; Datasets;
D O I
10.1145/3610978.3638163
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This workshop focuses on the understanding and modeling of social signals to create human-aware HRI. The three fundamental themes are: understanding social signals (gain insights into human internal states), modeling social signals for the generation of a human's mental state (translating social signals into actionable computational models), and operationalizing human models for human-aware applications (integrating these cognitive models into robotic systems to develop new human-aware capabilities). The invited speakers, paper presentations, and discussions will aim to focus on the social science background of social signals, acquisition and availability of benchmarking datasets, social signal modeling techniques, integration of models into real-time systems, usage of these models-such as error management, personalization, and mental model alignment-and applications of these models (i.e., healthcare, education, manufacturing). We expect these topics to demonstrate how modeling social signals, both explicit and implicit, is necessary for fluent, intuitive and trustworthy interactions.
引用
收藏
页码:1358 / 1360
页数:3
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