A Robot Training Buddy for adults with ASD

为患有自闭症谱系障碍 (ASD) 的成人提供的机器人训练伙伴

• 批准号: EP/N034546/1
• 负责人: Ruth Aylett
• 金额: $ 92.06万
• 依托单位: Heriot-Watt University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN034546%2F1
• 关键词: Robot; Training; Buddy; adults; ASD

Autism Spectrum Disorder (ASD) affects 695,000 people in the UK, and about 547,000 of these are 18 or over (1.3% of the adults in working age). The unemployment rate among adults with an ASD is higher than 85%, nearly double the unemployment rate of 48% for the wider disabled population. One reason for this is that people with an ASD struggle to interpret social signals, those expressive behavioural cues through which people manifest what they feel or think (facial expressions, vocalisations, gestures, etc.). This project will develop a Socially-Competent Robot Training Buddy that will help adults with ASD to better deal with social signals in work-related scenarios.The project is inherently interdisciplinary and falls in the new research area of Socially Assistive Robotics, at the crossroads between robotics, psychology, and social signal processing. So far, autonomous robots have largely been seen as functionally engineered to carrying out well-defined tasks in an efficient manner. However Socially Assistive Robots (SARs) must fit into normal human social environments and follow interaction rules that do not disrupt an office or a home or upset their human interaction partners. This project will focus on high-functioning adults with an ASD, and just as physically assistive robots enable people to make movements that are difficult because of physical impairments, the SAR of this project enables people with an ASD to perform social tasks that are difficult - if not impossible - due to social cognition impairments.The main goal is to reduce the cost of Behavioural Skills Training (BST) through the development of a Robot Training Buddy. BST is recognized as one of the most effective approaches to alleviate ASD effects, but cannot be applied extensively because it is labour intensive. Using an autonomous robot would reduce the human effort and cost of BST and make it more widely available. The main technological challenge is the development of a novel affective architecture that makes a robot suitable for behaviour rehearsal, a critical stage of BST. In behaviour rehearsal, the robot must reinforce the use of appropriate social signals by its human interaction partner while inhibiting the use of inappropriate ones. The team will work with stakeholders involved with training for adults with an ASD to develop workplace-relevant scenarios in which to develop and evaluate the Training Buddy with end-users.This work will develop the necessary scientific basis for the introduction of socially-competent robots into human social environments, opening the way to a multitude of domestic, educational and assistive applications.

自闭症谱系障碍（ASD）在英国影响着69.5万人，其中约54.7万人年龄在18岁或以上（占工作年龄成年人的1.3%）。患有自闭症谱系障碍的成年人的失业率超过85%，几乎是一般残疾人群失业率（48%）的两倍。其中一个原因是，自闭症患者很难理解社会信号，即人们通过这些信号表达自己的感受或想法（面部表情、声音、手势等）的表达性行为线索。该项目将开发一个具有社交能力的机器人训练伙伴，帮助患有自闭症的成年人更好地处理与工作相关的社交信号。该项目本质上是跨学科的，属于社会辅助机器人的新研究领域，处于机器人、心理学和社会信号处理的十字路口。到目前为止，自主机器人在很大程度上被视为在功能上被设计成以有效的方式执行定义明确的任务。然而，社会辅助机器人（sar）必须适应正常的人类社会环境，并遵循不会扰乱办公室或家庭或扰乱其人类互动伙伴的互动规则。这个项目将专注于患有自闭症谱系障碍的高功能成年人，正如身体辅助机器人使人们能够做出由于身体障碍而困难的运动一样，这个项目的SAR使自闭症谱系障碍患者能够执行由于社会认知障碍而困难的社会任务，如果不是不可能的话。主要目标是通过开发机器人训练伙伴来降低行为技能训练（BST）的成本。BST被认为是缓解ASD影响最有效的方法之一，但由于它是劳动密集型的，因此不能广泛应用。使用自主机器人将减少人力和BST的成本，并使其得到更广泛的应用。主要的技术挑战是开发一种新的情感架构，使机器人适合行为排练，这是BST的关键阶段。在行为预演中，机器人必须加强其人类互动伙伴对适当社交信号的使用，同时抑制不适当社交信号的使用。该团队将与参与ASD成人培训的利益相关者合作，开发与工作场所相关的场景，以便与最终用户一起开发和评估培训伙伴。这项工作将为将具有社会能力的机器人引入人类社会环境奠定必要的科学基础，为大量的家庭、教育和辅助应用开辟道路。

项目成果

An Architecture for Emotional Facial Expressions as Social Signals

• DOI: 10.1109/taffc.2019.2906200
• 发表时间: 2021-04-01
• 期刊: IEEE TRANSACTIONS ON AFFECTIVE COMPUTING
• 影响因子: 11.2
• 作者: Aylett, Ruth;Ritter, Christopher;Rajendran, Gnanathusharan
• 通讯作者: Rajendran, Gnanathusharan

Social Robotics

社交机器人

• DOI: 10.1007/978-3-319-70022-9_19
• 发表时间: 2017
• 作者: McKenna P

Robot expressive behaviour and autistic traits

机器人表达行为和自闭症特征

• 发表时间: 2018
• 期刊: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
• 作者: McKenna P.E.

Cultural Social Signal Interplay with an Expressive Robot

文化社交信号与富有表现力的机器人的相互作用

• DOI: 10.1145/3267851.3267905
• 发表时间: 2018
• 作者: McKenna P

On the privacy of mental health apps: An empirical investigation and its implications for app development.

关于心理健康应用程序的隐私：实证调查及其对应用程序开发的影响。

• DOI: 10.1007/978-3-319-10759-2_2
• 发表时间: 2023
• 期刊: Empirical software engineering
• 影响因子: 4.1
• 作者: Iwaya LH