Adaptive Robotic EQ for Well-being (ARoEQ)

幸福感自适应机器人情商 (ARoEQ)

• 批准号: EP/R030782/1
• 负责人: Hatice Gunes
• 金额: $ 111.04万
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR030782%2F1
• 关键词: Adaptive; Robotic; EQ; Well; being

Social robots are envisioned to interact closely with people safely and efficiently, and to add value to people's lives by helping, caring, teaching and entertaining. However, currently there is a major gap between public perception of humanoid / social robot capabilities and their actual capabilities. The cognitive and social capabilities of the current humanoid robots are still very limited.Although social robotics is an inherently multi-disciplinary field, there are no systematic efforts to develop novel sensing, perception and understanding capabilities for these robots grounded in the state of the art in the fields of affective computing, social signal processing, computer vision and machine learning. To avoid re-inventing the wheel, researchers in HRI often and rightly utilise available sensing / perception tools from other domains, creating their own in-house datasets and evaluations. However, these practices hinder advance in social robotics, leading to a major lack of novel and domain specific tools, and a lack of measures for benchmarking due to a lack of annotated, publicly available multimodal interaction datasets that are vital for comparative evaluation. This Fellowship aims to address these major gaps in HRI and social robotics. Its vision is to:(1) equip humanoid robots with novel socio-emotional intelligence and adaptation capabilities grounded in the state of the art in affective computing, social signal processing, computer vision and machine learning fields; (2) investigate the deployment of humanoid robots as socio-emotionally smart embodied personal devices that can potentially revolutionise our ability to maintain healthier behaviours and working environments, leading to resilient communities.

社交机器人被设想为安全有效地与人密切互动，并通过帮助、关怀、教学和娱乐为人们的生活增添价值。然而，目前公众对类人/社交机器人能力的认知与它们的实际能力之间存在很大差距。目前的类人机器人的认知和社交能力仍然非常有限。虽然社交机器人本质上是一个多学科领域，但在情感计算、社交信号处理、计算机视觉和机器学习等领域的最新技术基础上，还没有系统的努力为这些机器人开发新的传感、感知和理解能力。为了避免重复发明轮子，人力资源研究所的研究人员经常正确地利用来自其他领域的可用传感/感知工具，创建自己的内部数据集和评估。然而，这些做法阻碍了社交机器人的进步，导致主要缺乏新颖和特定领域的工具，并且由于缺乏对比较评估至关重要的注释，公开可用的多模态交互数据集而缺乏基准测试措施。该奖学金旨在解决HRI和社交机器人领域的这些主要差距。其愿景是：(1)在情感计算、社会信号处理、计算机视觉和机器学习领域的最新技术基础上，为类人机器人配备新颖的社会情感智力和适应能力；(2)研究将人形机器人作为具有社会情感智能的具身个人设备的部署，这种设备可能会彻底改变我们保持更健康行为和工作环境的能力，从而形成有弹性的社区。

项目成果

Can Robots Help in the Evaluation of Mental Wellbeing in Children? An Empirical Study

机器人可以帮助评估儿童的心理健康吗？

• DOI: 10.1109/ro-man53752.2022.9900843
• 发表时间: 2022
• 作者: Abbasi N

Humanoid Robots for Wellbeing Assessment in Children: How Does Anxiety towards the Robot Affect Perceptions of Robot Role, Behaviour and Capabilities?

用于儿童健康评估的人形机器人：对机器人的焦虑如何影响对机器人角色、行为和能力的看法？

• DOI: 10.1109/ro-man57019.2023.10309486
• 发表时间: 2023
• 作者: Abbasi N

Robotic Coaches Delivering Group Mindfulness Practice at a Public Cafe

机器人教练在公共咖啡馆进行团体正念练习

• DOI: 10.1145/3568294.3580048
• 发表时间: 2023
• 作者: Axelsson M

Statistical, Spectral and Graph Representations for Video-based Facial Expression Recognition in Children

基于视频的儿童面部表情识别的统计、光谱和图形表示

• 发表时间: 2022
• 作者: Abbasi N

Measuring mental wellbeing of children via human-robot interaction Challenges and opportunities

• DOI: 10.1075/is.21027.abb
• 发表时间: 2022-12-31
• 期刊: INTERACTION STUDIES
• 影响因子: 1.5
• 作者: Abbasi, Nida Itrat;Spitale, Micol;Gunes, Hatice
• 通讯作者: Gunes, Hatice