ThoughtWorks
  • 联系我们
  • Español
  • Português
  • Deutsch
  • English
概况
  • 工匠精神和科技思维

    采用现代的软件开发方法,更快地交付价值

    智能驱动的决策机制

    利用数据资产解锁新价值来源

  • 低摩擦的运营模式

    提升组织的变革响应力

    企业级平台战略

    创建与经营战略发展同步的灵活的技术平台

  • 客户洞察和数字化产品能力

    快速设计、交付及演进优质产品和卓越体验

    合作伙伴

    利用我们可靠的合作商网络来扩大我们为客户提供的成果

概况
  • 汽车企业
  • 清洁技术,能源与公用事业
  • 金融和保险企业
  • 医疗企业
  • 媒体和出版业
  • 非盈利性组织
  • 公共服务机构
  • 零售业和电商
  • 旅游业和运输业
概况

特色

  • 技术

    深入探索企业技术与卓越工程管理

  • 商业

    及时了解数字领导者的最新业务和行业见解

  • 文化

    分享职业发展心得,以及我们对社会公正和包容性的见解

数字出版物和工具

  • 技术雷达

    对前沿技术提供意见和指引

  • 视野

    服务数字读者的出版物

  • 数字化流畅度模型

    可以将应对不确定性所需的数字能力进行优先级划分的模型

  • 解码器

    业务主管的A-Z技术指南

所有洞见

  • 文章

    助力商业的专业洞见

  • 博客

    ThoughtWorks 全球员工的洞见及观点

  • 书籍

    浏览更多我们的书籍

  • 播客

    分析商业和技术最新趋势的精彩对话

概况
  • 申请流程

    面试准备

  • 毕业生和变换职业者

    正确开启技术生涯

  • 搜索工作

    在您所在的区域寻找正在招聘的岗位

  • 保持联系

    订阅我们的月度新闻简报

概况
  • 会议与活动
  • 多元与包容
  • 新闻
  • 开源
  • 领导层
  • 社会影响力
  • Español
  • Português
  • Deutsch
  • English
ThoughtWorks菜单
  • 关闭   ✕
  • 产品及服务
  • 合作伙伴
  • 洞见
  • 加入我们
  • 关于我们
  • 联系我们
  • 返回
  • 关闭   ✕
  • 概况
  • 工匠精神和科技思维

    采用现代的软件开发方法,更快地交付价值

  • 客户洞察和数字化产品能力

    快速设计、交付及演进优质产品和卓越体验

  • 低摩擦的运营模式

    提升组织的变革响应力

  • 智能驱动的决策机制

    利用数据资产解锁新价值来源

  • 合作伙伴

    利用我们可靠的合作商网络来扩大我们为客户提供的成果

  • 企业级平台战略

    创建与经营战略发展同步的灵活的技术平台

  • 返回
  • 关闭   ✕
  • 概况
  • 汽车企业
  • 清洁技术,能源与公用事业
  • 金融和保险企业
  • 医疗企业
  • 媒体和出版业
  • 非盈利性组织
  • 公共服务机构
  • 零售业和电商
  • 旅游业和运输业
  • 返回
  • 关闭   ✕
  • 概况
  • 特色

  • 技术

    深入探索企业技术与卓越工程管理

  • 商业

    及时了解数字领导者的最新业务和行业见解

  • 文化

    分享职业发展心得,以及我们对社会公正和包容性的见解

  • 数字出版物和工具

  • 技术雷达

    对前沿技术提供意见和指引

  • 视野

    服务数字读者的出版物

  • 数字化流畅度模型

    可以将应对不确定性所需的数字能力进行优先级划分的模型

  • 解码器

    业务主管的A-Z技术指南

  • 所有洞见

  • 文章

    助力商业的专业洞见

  • 博客

    ThoughtWorks 全球员工的洞见及观点

  • 书籍

    浏览更多我们的书籍

  • 播客

    分析商业和技术最新趋势的精彩对话

  • 返回
  • 关闭   ✕
  • 概况
  • 申请流程

    面试准备

  • 毕业生和变换职业者

    正确开启技术生涯

  • 搜索工作

    在您所在的区域寻找正在招聘的岗位

  • 保持联系

    订阅我们的月度新闻简报

  • 返回
  • 关闭   ✕
  • 概况
  • 会议与活动
  • 多元与包容
  • 新闻
  • 开源
  • 领导层
  • 社会影响力
博客
选择主题
查看所有话题关闭
技术 
敏捷项目管理 云 持续交付 数据科学与工程 捍卫网络自由 演进式架构 体验设计 物联网 语言、工具与框架 遗留资产现代化 Machine Learning & Artificial Intelligence 微服务 平台 安全 软件测试 技术策略 
商业 
金融服务 全球医疗 创新 零售行业 转型 
招聘 
职业心得 多元与融合 社会改变 
博客

话题

选择主题
  • 技术
    技术
  • 技术 概观
  • 敏捷项目管理
  • 云
  • 持续交付
  • 数据科学与工程
  • 捍卫网络自由
  • 演进式架构
  • 体验设计
  • 物联网
  • 语言、工具与框架
  • 遗留资产现代化
  • Machine Learning & Artificial Intelligence
  • 微服务
  • 平台
  • 安全
  • 软件测试
  • 技术策略
  • 商业
    商业
  • 商业 概观
  • 金融服务
  • 全球医疗
  • 创新
  • 零售行业
  • 转型
  • 招聘
    招聘
  • 招聘 概观
  • 职业心得
  • 多元与融合
  • 社会改变
物联网技术

How NAO robots can help children understand emotion

Lina Alagrami Lina Alagrami

Published: Oct 22, 2018

Autistic children can experience difficulties in relating to others and understanding emotions. Now, help is at hand, thanks to a mask-wearing, kid-friendly robot.

This is the work of London-based ThoughtWorker, Lina Alagrami — who explored this topic at XConf EU.

Having worked with NAO robots — the commercially available teaching robots from SoftBank for three years, after initially experimenting with them at Queen Mary University of London. Lina began working on a project to create an interactive application for an NAO robot that could work with autistic children to help them interpret different emotions.

According to studies by the UK’s NHS, autistic children can struggle to relate to other kids, as they find it difficult to understand the feelings and emotions displayed by others. This makes it hard for them to start or join in conversations. By minimizing the human element and introducing games with NAO robots into a learning programme, children are less likely to concentrate on physical interaction and instead focus on the learning and education that the robot provides.

Lina’s project, The Mask of eNAOtion, is based on the creation of a method to detect how different emotions are expressed. Lina’s aim was to help young children understand what the different emotions are and how to express them, to aid their interaction with other children.

Based on a ‘Simon Says’ style game, the NAO robot asks the child to copy a specified emotion (the prototype version of the game includes four emotions; happy, sad, angry and shocked), then checks to see if the child has successfully copied it. If not, the robot asks the child to try again until the emotion is successfully copied. When the child is successful, the NAO robot congratulates them and moves on to the next emotion.

Lina’s methodology for enabling the emotion detection was to create an LED mask (The Mask of eNAOtion) which was fitted to the front of the robot. The mask is made up of a matrix of LEDs spread across three PCBs. An integrated circuit controls the 40 LEDs which make up the ‘face’ on the robot’s mask. The integrated circuit can be controlled to set the LEDs using microcontrollers (such as an Arduino or a Raspberry PI), or USB to Serial modules, which were the preferred method for this project. The USB to Serial module allows the NAO robot to send specific commands to the integrated circuit, telling it which LEDs to turn on or off, creating the happy, sad, angry and shocked faces.

Q&A with Lina Algrami

What was the reaction when you tried out The Mask of eNAOtion game with children for the first time?

As the mask is a prototype it's not really that friendly looking; I tried it with my younger siblings, ages three and ten (both are not autistic).

At first, the three-year-old was confused as to why the robot was wearing the mask, but after explaining it's used to display different emotions as the robot doesn't really have a face, she moved past it and continued to play the game.

When displaying the different emotions, she found it easy to get happy, angry and shocked but struggled with sad. For her, sad meant crying, not frowning — and that's what the robot was displaying. I had to explain she needed to copy what the robot was showing on the mask. The ten-year-old had no problem playing the game, but being surrounded by his family when it came to displaying these emotions, he'd laugh and so the robot would ask him to try again. Once again, sad was one that was tricky.

If you were doing this project again, what would you do differently?

The first thing I would do differently is the mask design. The NAO robot has two cameras (top and bottom), for this game, the bottom one had to be disabled as it's covered by the mouth PCB. For better emotion detection, using both cameras would be better, so I'd like to explore different mask designs that'll allow enabling the bottom camera. I'd also look into wireless communication between the robot and the LEDs — maybe using Wi-Fi or sound recognition (from the robot) to control the mask.

What was the biggest learning?

I specifically chose this project because it combines both hardware and software. So I'd say the whole thing was full of learning, from really digging into the different USB to Serial devices and the different protocols, all the way to emotion detection and finding the perfect threshold for different emotions. But if I had to narrow to just one learning, it would definitely be don't trust hardware — one loose wire can ruin everything!
 
相关博客
Machine Learning & Artificial Intelligence

Recognizing human facial expressions with machine learning

Angelica Perez
了解更多
Machine Learning & Artificial Intelligence

How artists are reshaping emerging technology research

Andrew McWilliams
了解更多
Machine Learning & Artificial Intelligence

How art programs drive innovation at ThoughtWorks

Andrew McWilliams
了解更多
  • 产品及服务
  • 合作伙伴
  • 洞见
  • 加入我们
  • 关于我们
  • 联系我们

WeChat

×
QR code to ThoughtWorks China WeChat subscription account

媒体与第三方机构垂询 | 政策声明 | Modern Slavery statement ThoughtWorks| 辅助功能 | © 2021 ThoughtWorks, Inc.