Must-have IT Features
Sensing (7x24) Mobility (autonomous)
社交保持 (~15%)
•Search for latest news and their relatives/friends’ SNS information, filter and summarize, then present to elderly in an easy way •Help elderly post their status on SNS, record happy moment •Help elderly do video chat with relatives/friends
健康可穿戴设备
Sensing (7x24) Mobility (autonomous) Wireless/Internet access Cognitive computing Natural user interaction Telepresence (A/V/move) Physical manipulation
Home IOT Devices
AOAC module RGBD camera
WiFi + Big BT storage
Health Wearables
Microphone Other array sensors
跌倒检测?
Smart Phone Apps
9/25/2015
INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
LIDAR与vSLAM对比
Capability Location error (cm) Tolerate lightness change Can handle black area Can handle glass area Can handle texture-less area Can handle thin object Color information Map information Real-time Cost Easy to deploy LIDAR <1 or ∝ Yes No No Yes No No Yes Yes Expensive Yes Takeaway: Neither is perfect, but combining them can get all “YES”. vSLAM <5 or ∝ Hard Yes Yes No Yes Yes Yes No Median to low Yes
9/25/2015 INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
2
照料者危机(Caregiver Crisis)催生需求
• 照料者的困难 >50%有全职工作 需要住在20分钟响应 范围内
•
目前可用技术 智能手机应用 IOT设备 可穿戴设备
• 对老人、病人和照料者来说既是医疗问题，也是社会问题
Physical manipulation*
* Manipulation is nice to have in the first stage
9/25/2015
INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
4
智能手机应用、IOT和可穿戴设备的差距
智能手机应用
Sensing (7x24) Mobility (autonomous) Wireless/Internet access Cognitive computing Natural user interaction Telepresence (A/V/move) Physical manipulation
家庭健康服务机器人的关键技术
宋继强 英特尔中国研究院
养老服务成为全球问题
年龄> 65 现在：2.12亿 年龄 > 60 连续增长·15 年 到底峰值4亿
2010年全国人口统计
• 巨大社会问题 巨大市场机会（政府支持） • 全球万亿级市场，但先进IT技术渗透率很低 • 绝大部分老人及其家人偏向于居家养老
• •
Raw data: daily volume: ~730MB, annual volume: ~260GB Assuming robot refresh cycle = 3 years, local storage size should > 1TB
9/25/2015
INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
9/25/2015 INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
3
家庭健康服务机器人（HSR）的功能需求
健康与情感关怀 (~80%)
•Voice chat with elderly, with memory-based personalization •Use words, graphics, sounds, lights to improve elderly’s mood •Recommend proper physical activities to elderly •Remind their relatives and friends to give care
Wireless/Internet access Cognitive computing Natural user interaction Telepresence (A/V/move)
紧急救助 (<10%)
•Detect anomaly from visual, aural and other input (like fall down, painful facial expression, big sound, etc.) •Do something according to first-aid guide for robots (like call someone, open window if poison gas is around) •Allow remote telepresence to let human judge and operate
注：3颗星表示功能足够好
局限： 没有一个是多传感、自主移动、本地智能运算 和远程呈现的自然整合。
9/25/2015
INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
5
HSR是终极解决方案
HSR
Aging care usages
Speech UI Core ix CPU Motion platform Visual UI Social Personalization I/O HW ACC Plan & control
Reminder Recommendation Anomaly detection
Social activity logging Location logging Conversation records logging Environmental data logging
Domainspecific Mining
◦ Object identification and manipulation ◦ Interplay with SLAM to help navigation
9/25/2015
INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
8
移动技术：在动态环境中自主移动
LIDAR‐based SLAM • 目前最便宜的RPLidar: RMB2400 • 360°, 6M, one‐plane map
家庭IOT设备
Sensing (7x24) Mobility (autonomous) Wireless/Internet access Cognitive computing Natural user interaction Telepresence (A/V/move) Physical manipulation
Think with memory
Jeff Hawkins: “memory + prediction” generates real intelligence. ‐‐ 《On Intelligence》 ‐‐《人工智能的未来》
13
家庭健康服务机器人的多维记忆
Environment Activity Video, image
7
视觉技术：从看见到理解
人脸，人 体识别
为了更好地与人交互
◦ Find people, recognize people, follow people ◦ Understand human activity ◦ Detect events ◦ Detect mood
物体识别
为了更好地与环境交互
障碍检测
Conversation Health
9/25/2015
INTEL CONFIDENTIAL ‐ INTERNAL USE ONLY
14
记忆的原始数据量估计
Data source Fixed-interval picture (day) Fixed-interval picture (night) Event-triggered picture Activity video (avg. 30 seconds) Conversation (avg. 60 seconds) Health data Environmental data Unit size (MB) 0.5 0.5 0.5 2 0.5 0.001 0.001 Frequency/hour 60 15 ~10 2 6 0.2 60 Hours 16 8 16 16 16 15 24 Daily volume (MB) 480 60 80 64 48 0.3 1.44